Center for Product Development

Center for sensing technologies

Project aim: agROBOfood is dedicated to the acceleration of the digital transformation of the European agri-food sector through the adoption of robotic technologies.
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About the project: agROBOfood will consolidate, extend, and strengthen the current ecosystem by establishing a sustainable network of Digital Innovation Hubs (DIHs). This will boost the uptake of robotic solutions by the agri-food sector: a huge challenge requiring an inclusive approach involving all relevant European players. The agROBOfood consortium consists of 39 partners, led by Wageningen University &amp; Research and other core partners of previous key projects such as IoF2020, ROBOTT-NET, PicknPack and I4MS, to leverage the ecosystem that was established in those projects. The heart of the project is formed by Innovation Experiments (IEs), organized, and monitored by the DIHs. In each of the 7 Regional Clusters, an initial IE will demonstrate the robotics innovations in agri-food in a manner that ensures replicability across Europe, wide adoption, and sustainability of the DIHs network. agROBOfood will work in lockstep with the European robotics community, ensuring synergetic effects with initiatives such as EU-Robotics. This will maximize the return of European investments, including private capital, in the digital transformation of agri-food. A key instrument to achieve this objective is the Industrial Advisory Board. They will provide strategic guidance and define priorities for the selection of solutions to be funded. Open Calls of 8MEUR will attract additional partners, which will expand the network and ensure that vast technological developments and emerging challenges of the agri-food sector are incorporated in the service portfolio of DIHs. Through its inclusive structure and ambitious targets, agROBOfood aims to bring the entire European ecosystem together; connecting the dots in a way that ensures effective adoption of robotics technologies in the European agri-food sector.
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Milica Trajković

Nikica Marinkovic holds degree engineer in Agriculture – Agri-management, University of Novi Sad. He has experience in various projects - agriculture, local economic development and in IT sector. His professional career includes 3 founded startups and he is „Global innovator“ named by EXPO 2020 Dubai for eco-packaging made of low quality wool as natural insulation - natural alternative to styrofoam food transportation boxes. Also, he has experience in agriculture SME sector as director of agriculture company specialized in fruit production. Improved knowledge in the area of agriculture in Italy and Israel, passionate about social entrepreneurship with focus on food and food chain supply.

Nikica Marinković

Branislava Davidović obtained a Master’s degree in Pedagogy at the Faculty of Philosophy, University of Novi Sad, Serbia. She has previously worked for private companies in various industries as an administrator and later as a referent of commercial and financial affairs. After that she started working at the NGO sector. She was working there for over ten years and had the opportunity to improve her skills and gain experience in proposal writing, project implementation, administration and financial management, and preparation of financial reports. The projects she worked on were supported and implemented in cooperation with the City Administrations of the City of Novi Sad and the Ministries of the Republic of Serbia. In November 2022 Branislava joined the BioSense team and currently, she is working as a Project Management Assistant at the Center for Innovation and Business Development at the BioSense Institute. She is actively involved in project agROBOfood.

Branislava Davidović

Kristina Petrović is a project manager at the Center for Biosystems at the BioSense Institute. She received her Ph.D. from the Faculty of Agriculture, the University of Belgrade, in 2013, on the topic of characterization of phytopathogenic fungi that cause soybean disease complex. Kristina Petrović has experience in various methods of characterizing soybean diseases. Her research is related to finding soybean resistance to pathogens, which is essential in agriculture, the food sector, and environmental protection. During 2010 and 2011, she attended the Centro di Ricerca per la Patologia Vegetale (CRA-PAV) in Rome, Italy, for professional training in the field of molecular characterization of phytopathogenic fungi, and completed postdoctoral specialization at the South Dakota State University, Brookings, USA, during 2017 and 2018. She has participated in several national and international projects and was the work package coordinator within the European ECOBREED project H2020. Kristina Petrović is the author or co-author of 90 scientific papers in international and national journals, a book of abstracts from international and national conferences, and patents. She is a member of the European Legume Hub Association Board, The American Phytopathological Society, The Australasian Plant Pathology Society, and the Plant Protection Society of Serbia.

Kristina Petrović

Snezana Djuric, Senior Research Associate, received PhD from the Faculty of Technical Sciences, University of Novi Sad, Power, Electronic and Telecommunication Engineering (Electronic) in 2013. Her research interests are bioelectronics systems, sensors, energy storage and energy harvesting, inductive systems and components.

Snežana Đurić

Slobodan Birgermajer is research associate in the Center for Sensing Technologies at the BioSense Institute. Mr. Birgermajer received his PhD in microware electronics form the Faculty of Technical Sciences, University of Novi Sad, in 2019. He is currently working on development and application of the sensors in agriculture, food industry, and environmental monitoring, and he is actively involved in many H2020 projects such as ANTARES, IPANEMA SHealty, etc. His main research interest includes microwave passive devices, photonic crystals, microfluidic sensors, and 3D and 4D printing.

Slobodan Birgermajer

Mina Mirović is a junior reseacher at BioSense Institute. She holds a BSc in Mechatronics from Faculty of Novi Sad and MSc in Mechatronics, Robotics and Embedded Systems from London South Bank University.

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Mina Mirović

Jovana Stanojev is a research assistant and a PhD student at the Faculty of Technology, University of Novi Sad. She studied materials engineering. She is working towards finishing her PhD thesis. Topic of her PhD thesis is "Development of uncooled infrared detector based on lead selenide". Her current research focuses are development of new materials for sensors, nanomaterials and nanomembranes, microfluidics, development of organ-on-a-chip platforms, cell culturing.

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Jovana Stanojev

Goran Kitić works at the position of the Head of the Center for Sensing Technologies within the BioSense Institute. He received a PhD degree from the Faculty of Technical Sciences, University of Novi Sad, Serbia in 2016 on the subject of microwave soil moisture sensors. Goran Kitić developed experience in the field of different fabrication technologies (LTCC, thin&amp;thick film technology, microfabrication, PCB, wire bonding, machining, and 3D printing) and characterization methods (electron microscopy, EDS spectroscopy, UV/Vis spectroscopy, optical profilometry, electrical measurements). His research interests are related to the development of sensors applied in agriculture, food sector and environmental protection. Some of the developed sensor prototypes involve a multispectral sensor for plant status assessment, soil moisture sensor, a device for early mastitis detection, nitrates in water detector. Besides stated, he is heavily involved in the development of a robotic system for soil sampling and analysis. His research work resulted in seven international journal publications, and numerous papers published on international conferences. During his research career, he was involved in 13 international and national projects.

Goran Kitić

Damir Krklješ works as a Senior Researcher at the BioSense institute. He received PhD at the University of Novi Sad, Faculty of Technical Sciences, Novi Sad, Serbia, in 2016. He worked as a research and teaching assistant at the Faculty of Technical Sciences, teaching electronics, sensors and actuators and mechatronics. During that time he participated in many national and international projects, where his main research topics involved robotics (sensorized, two degree of freedom gripper. Sensorized robotic foot for ZMP measurement), force sensors (optical and force sensing resistors) and capacitive angular speed and position sensors, based on printed flexible substrates. Starting in 2013 he moved to the industry, where he worked for a few companies, mostly in a design service area for leading worldwide industrial partners. He was engaged both, as an engineer, and as a head of the department. During that period he was involved in a development of industrial products involving high-end LED lightning digitally controlled power converters, sophisticated devices for water pumps monitoring, power converters, etc. Damir Krklješ published over 30 journal and conference papers.

Damir Krklješ

Csaba Petes received his MSc degree in 2017 from the Faculty of Technical Sciences, Department of microprocessor systems and algorithms, University of Novi Sad, Serbia. His Master thesis: Remote control of moving vehicles using DTMF codes and the video signal on large and small distances.
Csaba received his BSc degree at the Faculty of Technical Sciences, Department of Microcomputer Electronics, where he graduated in 2014. Graduation thesis: Development and implementation of program "Paint" on embedded system. After his college, he founded his own company (Sept 2013), the Consulting Agency Starprofit which represented the Güttler GmbH in Serbia and other foreign companies on Serbian market, mostly in agriculture business.
In parallel he worked as a sales manager and as a teacher of the High School "Mihajlo Pupin" and Technical School in Bečej from October 2014 until September 2017. Now he works at the Biosense Institute on Embedded software and robotics systems. He is on more projects (Antares, MIMA, AgroboFood, WaQuMoS) .
In those projects, Csaba Petes take part primarily in the development of analog and digital electronics for read-out system, design PCB layouts, realization PCB prototypes, supporting the overall design of the robot, integration and signal processing.
Contact address: petes.csaba@gmail.com or chaba@biosense.rs

Čaba Peteš

Milijana Vujasinović is the head of Product Development Center. She has many years of experience in development and implementation of software solutions. In the development of software solutions, she was initially involved as a programmer and business analyst, and later as a solution designer and product manager. She gained a lot of experience working as an ERP consultant and project manager in implementation of software solutions in different industries – agriculture, wholesale and retail chains, food, textile, metallurgy, tool and cable, construction, service industry, metallurgy and public companies. She has SAP Financial Accounting certificate and SAP Project Manager certificate. For more than 3 years, she managed PMO (Project Management Office), the department that controls and improves the project management process.

Milijana Vujasinović

Maša Mimica works as a Project Manager at BioSense Institute, covering two equally important fields – H2020 financial management and project management of cascade funding projects. She has extensive experience in financial reporting at the project level, portfolio of 17M€ with a proven track-record in planning, reporting and analysis of business needs and other financial aspects of the Institute. Maša as part of Business Development Department collaborates with other cross-finance teams in driving strategic decisions and ongoing operations.
In parallel, Maša acts as a Project Manager for cascade funded sub-projects, previously in FP7 and now in H2020 programme. Thus, she has a vast experience in tailor-made innovation and acceleration activities, which led to market positioning and expansion of more than 150 SMEs, cross-cutting IT and agricultural sectors.
Maša has strong background in multinational environment, where working with different stakeholders across the board in various industries, contributed to the development of her business and interpersonal skills.

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Maša Mimica

Ms. Isidora Stojačić (F) works as a Project Manager at the Business Development Department at BioSense Institute. She obtained her bachelor’s degree at the University of Novi Sad, Faculty of Economics, and her master’s degree at the University Cattolica del Sacro Cuore, Faculty of Agriculture and Life
Sciences and at the Technical University of Munich, Faculty of Life Sciences. She has a few years of experience in project management, research, and project proposal writing. She has been involved in various topics, mostly related to Responsible Research and Innovation, co-creation, social design and implementation, market and business exploitation and multi-actor engagement strategies. She has been involved in Horizon2020, ERASMUS+ and National projects.

Isidora Stojačić

Ms. Dragana Petković (F) works as a Project Manager at the Business Development Department at BioSense Institute and as the coordinator of BioSense Accelerator for early-stage agri-tech startups. She graduated from the Faculty of Political Sciences in Belgrade. She is the co-founder of the Coworking Association of Serbia, one of the founders and former executive director of Startit, leading IT and startup support organization in Serbia. Previously she worked as a consultant on various entrepreneurial ecosystem development projects with GIZ and Port of Belgrade, and she worked as a mentor and consultant for startups in different industries.

Dragana Petković

Željana Grbović is a young researcher and PhD student in electrical engineering at University of Novi Sad, Faculty of Technical Sciences. She is highly interested in the application of machine learning algorithms and deep learning in the field of agriculture. Her beginnings in machine learning started 2016 when her team ranked in the top 5 among 52 teams in the prestigious competition SP Cup organized by IEEE. She received her master’s degree with the thesis about ear detection in wheat thermal images using deep neural networks. She has expanded the field experiment on the wheat involving images from mobile phones to provide early prediction. She has got funding from Innovation Fund, for The Proof of Concept for her PhD research topic. She is a guest researcher at Wageningen University and Research (WUR) in the group of Computer Vision and Agro-Food Robotics. She was involved in a Humistatus project about the prediction of spreading fungal infection on tomatoes based on hyperspectral images funded by the company Green Yard and WUR. She was a member of the team who tested PerClass MIRA Software for hyperspectral image processing before it was launched as public. Her main interests are image processing and application of transfer deep learning in plant phenotyping, food quality and safety. She is an active member of the artificial intelligence community and was invited speaker on several meetups and conferences where she promoted obtained results on phenotyping. She was a leader of a team that won third prize in the national competition „Space4Women“. Also, she led a team that participated at Alibaba Get Global Challenge final competition. She is actively involved in a few Horizon 2020 projects including ANTARES, Cybele, Dragon (serves as Dissemination Manager) and AgROBOfood and a few industrial projects with partners.

Željana Grbović

Predrag Matavulj is a doctoral student of Informatics with strong knowledge in probability theory and statistics, numerical optimization, machine learning and neural networks, most of which he acquired during his Bachelor studies in Mathematics and Master studies in Data Science at Faculty of Sciences, University of Novi Sad. While working on his Master’s thesis, in March 2018, Predrag started his work as a junior researcher at BioSense Institute, where he utilized deep learning techniques to identify and classify bioaerosols. Since November 2018 Predrag has been teaching deep learning as a teaching assistant responsible for the Data Science Master’s course at the Faculty of Sciences. He is involved in several national and international projects including Antares, Dragon, agROBOfood, PROMIS.

Predrag Matavulj

Oskar Marko, Ph.D. is the Head of the Center for Information Technologies and the Assistant Director for Innovation and Cooperation with the Economy at the BioSense Institute. His research focuses on applying advanced machine learning and evolutionary algorithms in agriculture. He spent the 3rd year of his undergraduate studies at City University London, where he did his final BEng project in signal processing. He led BioSense’s team that developed novel Big Data algorithms for yield prediction, seed distribution, and optimization of sowing strategies, which secured the 1st prize for BioSense at the Syngenta Crop Challenge and CGIAR Inspire Challenge. He is actively involved in many Horizon 2020 projects including Antares, Cybele, Dragon, and Flexigrobots, and industrial projects with partners such as Krivaja, MK Agriculture, Delta, and other farming and insurance companies.

Oskar Marko

Mirjana Radulović is a Junior Research Assistant at the BioSense Institute with interests in remote sensing, geoinformatics, water resource management, agriculture, and the environment. She is currently enrolled as a Ph.D. student of Geosciences at the Faculty of Sciences, the University of Novi Sad where she also received her BSc (2017) and MSc (2018) in the field of hydrology and geoinformatics. During master studies, she spent five months at the Palacký University in Olomouc (Czech Republic) where she studied as a scholarship holder of the Erasmus+ Exchange Program. In March 2019 she joined the BioSense Institute where she works on applying geographical information systems and remote sensing tehnology for monitoring of irrigation, drought monitoring, crop monitoring, land use classification, groundwater monitoring, etc. She participates in several national and international projects related to these topics. Mirjana authored and co-authored several scientific papers and attended several scientific conferences.

Mirjana Radulović

Miloš Pandžić is a Junior Research Assistant whose interest includes several research fields: Earth observation, remote sensing, image processing and data analytics. He is currently enrolled as a PhD student of Geodesy and Geoinformatics at the Faculty of Civil Engineering, University of Belgrade, where he also obtained his master and bachelor degree. In 2015 he received scholarship from the Government of Austria (OeAD) and spent 4 months at TU Vienna where he analysed geometric quality of Sentinel-2 satellite multispectral images. Outcome of this work was his master thesis. After graduation he worked at the Finnish Geospatial Research Institute (FGI) on several projects funded by Academy of Finland and European Space Agency (ESA). His main occupation was segmentation and change detection in satellite imagery related to agricultural activity, urbanization and deforestation. In 2018 he joined BioSense Institute where he works on data fusion of optical and radar images for yield prediction, crop classification, crop monitoring, etc. He is involved in several national and international projects including Antares, Cybele, Dragon, PARSEC, agROBOfood.

Miloš Pandžić

Dr. Marko Panić is a research associate in the field of technical sciences and information technologies at the BioSense Institute. His doctoral dissertation is related to the development of algorithms for accelerated image reconstruction from incomplete measurements using a sparse representation of signals and statistical Markov random models. His research direction includes statistical modeling of multidimensional data obtained from different sensors. He is currently working on the analysis and processing of images obtained from hyperspectral and multispectral cameras using advanced machine learning methods with application in assessing the quality of fruits and vegetables. As a member of the BioSense team, he participated in Syngenta's "Crop Challenge" competition, which resulted in winning first place. He is actively involved in many projects from the Horizon 2020 call, including Antares, Cybele, Dragon and Flexirobots, as well as in projects with companies such as Krivaja, MK Agri and Delta Agrar.

Marko Panić

Dragana Blagojević obtained BSc (2017) and MSc (2018) degrees in geography at the Faculty of Sciences in Novi Sad with a focus on geographic information systems and their use in the hydrological and geomorphological analysis. In October 2018, she enrolled in Ph.D. studies in Geosciences at the same faculty. She spent the summer semester of the master studies at the Palacký University in Olomouc (UPOL) in the Czech Republic, as a scholarship holder of the Erasmus+ Exchange Program where she studied at the Department of Geoinformatics. In January 2019 she joined BioSense Institute where she works as a Junior Research Assistant in the Centre for Information Technologies. Her research area is in the field of remote sensing, precision agriculture, yield monitoring, and mapping as well as filed work analyses. Her research aim is an integration of these techniques to get complete and precise information about filed, crops, terrain, and soil characteristics.

Dragana Blagojević

Branislav Pejak is a PhD student of Electrical Engineering at the Faculty of Technical Sciences, the University of Novi Sad, where he also received his BSc (2017) and MSc (2018) in the field of Biomedical Engineering. During his bachelor and master studies, he held a scholarship from the Ministry of Education, Science and Technological Development, Republic of Serbia. Since March 2018, Branislav has been working as a Junior Research Assistant at the Center for Information Technologies, BioSense Institute. His main research is data analytics on satellite images. Currently he is working on crop classification and crop yield prediction using time series of multispectral images and GAN machine learning framework. Within the project he is also working on many practical usages of ICT in agriculture such as smart soil sampling and fertilization, irrigation zone mapping, grain yield and protein content prediction etc. He is actively involved in many Horizon 2020 projects including Antares, Cybele, Dragon and AgRoboFood.

Branislav Pejak

agROBOfood logo

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This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 825395.


Horizon 2020

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BioSense Institute (Institute for Research and Development of Information Technology in Biosystems) is a leading Serbian Digital Innovation Hub (DIH) focused on bringing together various stakeholders from industry, field of research, entrepreneurial community and the general public. As such, BioSense acts as a one-stop-shop, providing competitive services and introducing digital innovations while connecting research, entrepreneurship, science and market-ready solutions.

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Since the DIH ecosystem in Serbia and the region is still in the early stages, BioSense works towards fulfilling its mission of bringing digital solutions to the broad farm-to-fork value chain. This is achieved by capitalizing on the strong technical talent, its scientific excellence and its understanding of the market. By using these three aspects, various activities are undertaken by BioSense staff while supporting the development of new in-house solutions, as well as those coming from the community built around the Institute. Innovations supported by BioSense are explored among farmers, advisory services, entrepreneurs, high schools, university graduates and professors. The lean multi actor approach allows for innovation to be deeply knitted into various parts of society while allowing our stakeholders to contribute to the way we innovate by giving us valuable feedback and needs for further advancement.

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Three types of services are at the core of BioSense DIH activity: business, technical and ecosystem. In addition, ongoing training, and skill development, perceived as DIHs umbrella activity, is equally targeting all three core pillars. This means that external parties can receive support while developing their technical solution, receiving business advice, or by being introduced to relevant partners and communities. These services are delivered through different activities, both project-based and commercial. In achieving so, the <a href="/en/collaborate/living-lab?id=88">PA4ALL Living Lab</a> facilities can be an enabling environment for prototyping, while the <a href="/en/collaborate/biosense-accelerator?id=1827">BioSense Accelerator</a> offers guidance for AgTech entrepreneurs in the early idea stage.

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Activities and accomplishments of BioSense DIH have been recognized both in Serbia and internationally. Since 2015, BioSense has been involved in some of the largest DIH based projects such as, IoF2020, SmartAgriHubs, agROBOfood and DIATOMIC. Our DIH is also part of <a href="https://smartanythingeverywhere.eu/">Smart anything anywhere</a> initiative, supporting SMEs with access to funding and expertise. In addition, the Institute works with large multi-national corporate stakeholders from various industries such as computer software, gaming and insurance, national bodies such as the Ministry of Agriculture, Forestry and Water Economy and the Cabinet of the Prime Minister as well as with citizens, farmers, educational institutions, other DIHs, policy makers, etc. Through these projects and activities, BioSense has not only contributed to digitizing the Serbian society but has also made a Europe-wide impact and continues to work on pioneering technologies and solutions.

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If you are interested in learning more about BioSense DIH, want to know more about the services offered or would like to cooperate with us, you can reach us Trajkovic[at] <a href="https://api.biosens.rs/en/employees/milica-trajkovic-2/">biosense.rs</a>.

Digital Innovation Hubs

Launch your AgTech idea!

BioSense Accelerator is an intensive 3-month program that targets early-stage AgTech startups and acts as a bridge between science and business. It is an excellent opportunity for startups to bring their bold AgTech ideas to life, grow, fast track their journey, and solve key challenges in the agrifood sector. The accelerator is the only one in the country that provides support to domestic and regional IT entrepreneurs focused on creating innovative and groundbreaking digital solutions for agriculture.
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The first batch of BioSense Accelerator started in October 2019 and over the course of three months that were jam-packed with interactive workshops and bespoke trainings, 8 teams mastered multiple skills: how to develop a business idea, define a business model, identify the needs of future users and conduct detailed analysis of the market and competition. Top-notch tech and business support, as well as guidance from industry and technology experts brought startups and their ideas to the next level. In the second batch (2020), we are joining forces with EFSE Fund and the best B2B accelerator in Europe, Startup Wise Guys.
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Besides a comprehensive support, BioSense Accelerator has given the teams a get-ready guide for fundraising, and startups that participated in the first batch raised 140K Euros over a period of six months.
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The idea of BioSense Accelerator is to boost entrepreneurial mentality in our country and subsequently, that will lead to economic growth and development. The goal is also to motivate regional IT entrepreneurs to be bold and create their own products.
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Find out more: <a href="http://accelerator.biosense.rs/">BioSense Accelerator</a>
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BioSense Accelerator

With the advancement of variable rate technologies (VRT) used for sowing, watering, fertilizing, pesticides and herbicides application, the need for systems that can precisely and quickly determine soil variability and identify management zones within a single plot emerged.

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We address this complex task using robot platform Agrobot Lala, which is specially adapted for agricultural applications as well as for incorporating sensors for soil analysis and soil sampling systems. The proposed system moves through the field and perform soil sampling and soil parameters analysis as well as the georeferencing the results of the analysis. The complete process is autonomous since it is possible to predefine the route of Agrobot Lala on the plot using GPS coordinates and a 3D Real-Time-LIDAR system.

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As a result of the analysis, multilayer maps are generated, which can be used to make the right decisions, optimize the production and make full use of the precision agriculture in terms of efficiency, yield increase and sustainability of agricultural production.

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Projects:

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agROBOfood: Business-Oriented Support to the European Robotics and Agri-food Sector, towards a network of Digital Innovation Hubs in Robotics, H2020-DT-2018-1

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Development of the device for measurement and mapping of nitrogen as the most important parameter in sustainable agriculture, contract no. 114-451-2794/2016-03, funded by Provincial Secretariat for Higher Education and Scientific Research of Autonomous Province of Vojvodina, Republic of Serbia.

Agrobot for in-field soil analysis

Agricultural robotics is a field that is becoming more and more mature, with new solutions constantly reaching the market. This area has seen a significant growth due to the shortage in workforce, high costs of labour and tediousness and repetitiveness of the tasks. BioSense uses robots as moving platforms for gathering the data about the crop production. These platforms are equipped with both commercially available sensors and sensors developed by the Group for Sensor Design.

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The latest project we have been working on is concerned with soil in-field analysis. The proposed system moves through the field and perform soil sampling and soil parameters analysis (macronutrients, micronutrients, pH, EC) as well as georeferencing of the results of the analysis. The complete process is autonomous since it is possible to predefine the route of robotic platform on the plot using GPS coordinates and a 3D Real-Time-LIDAR system for reconstructing the surrounding area and avoiding any possible obstacles. As a result of the analysis, multilayer maps are generated where each layer represents one of the parameters obtained by the proposed system. Based on these maps, the farmer will be able to make the right decisions, optimize the production and make full use of the precision agriculture in terms of efficiency, yield increase and sustainability of agricultural production.

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Robotics

At Biosense Institute we are using quadcopter DJI Inspire 1 to gain better insight into crop production and plan and manage agricultural operations more accurately. The technology can collect very high-resolution imagery below cloud level, with much more detail than the satellite imagery. The datasets include images captured with RGB and modified NDVI camera, but we are also using Flir thermal camera to make temperature measurements over large areas of heterogeneous terrain. Unmanned aerial vehicles are easy to use, as most mapping and data-collection missions are now conducted autonomously, by feeding the shape file of the desired area into the dedicated software.

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For image stitching we use Pix4D and AgisoftPhotoscan software to generate high-resolution orthomosaics, vegetation index maps and DSMs (Digital Surface Models). These orthomaps are important layers of information and they can be integrated into GIS systems along with other layers derived from additional sources. These datasets are then processed and used for training of advanced machine learning algorithms.

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BioSense uses UAS (Unmanned Aerial Systems) to detect nutrient deficiencies, pest infestations, water stress or excess and other conditions that affect crop development and improve the management of crops. They are especially useful for fields of a few dozens of hectares, such as orchards or vineyards, as scanning large fields of arable crops requires a lot of time. UAVs have also proven as effective tools for environmental monitoring, as they can cover medium-sized habitats and tell us more about the type of surroundings that insects and mammals grow in. The use of UAVs revolutionized spatial ecology and agriculture and allowed us to get high-resolution data and make optimal decisions with high accuracy.

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NDVI map of sugar beet crop

Drone Imaging

BioSense is the location of a Sentinel Data Hub and we are an active user of products from the ESA’s Copernicus programme. Before the launch of Sentinel satellites, our research was based on Landsat 7 and 8 and RapidView images, but today, it is mainly focused on data coming from Sentinel 1 and 2 missions. Images from Sentinel 2 are coming in 13 spectral bands, approximately every 5 days, depending on the cloud coverage, while Sentinel 1’s synthetic aperture radar allows for monitoring even in the case of clouds. This ensures continuous high-resolution monitoring of the environment and agricultural production in particular, throughout the growing season.

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Since 2012, we have been producing land-cover maps for the Serbian province of Vojvodina, which distinguish fields of different crops, urban areas, forests and water bodies. This allowed us to map animal habitats, observe their change and capture the trends in crop rotation. Using the principles of data fusion, we reached the sub-pixel resolution using data sources with heterogeneous pixel grids. The second line of research is concerned with yield prediction. Based on the ground truth coming from field records, crowdsourced data and yield maps, we are training advanced machine learning models to estimate the yield. These models are based on more than 30 satellite vegetation indices, that incorporate the domain knowledge about the crops, and their accuracy is increased as plants progress through phenological stages. Vegetation indices are also excellent proxies for the damage assessment, as some of them are excellent proxies for damage caused by hail, drought or fire. This puts insurance companies among our partners, along with the government, research institutions and, nevertheless, the farmers, who are using our results to optimise the decisions concerning the time and amount of irrigation and distribution of fertilisers and pesticides.

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Satellite imaging

European Space Agency (ESA) has launched a constellation of Sentinel satellites through Copernicus programme. With €7 bn investment, it is the most ambitious programme of Earth observation in the history of space exploration and the satellite data have found wide application in climate change monitoring, civil engineering, and emergency response during extreme weather events. Data generated through this project are completely free and open for everyone. It is also believed that the European economy will generate €30 bn by 2030 through companies based on satellite data analytics. Due to the huge boost that Copernicus will give to high-tech start-ups and companies, people are often talking about the “Copernicus economy”.

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In 2017 Serbia has become the only country that as an associated member of the EU has a wideband access to ESA’s images. “Sentinel Data Hub” founded at BioSense Institute receives the data from satellites and these data are processed on high-performance servers. For the dissemination of satellite images, DHuS (Data Hub Software), a Java-based software, is used. It is an open-source software that enables user-friendly web environment for interactive discovery and download of data, as well as an excellent application programming interface (API), that allows users to access the data through their programs, scripts and client applications. In this way, the download is automated and the imagery became available to everyone around the world.

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ESA’s images have been widely used at the Institute for development of crop classification maps, yield prediction and growth monitoring using numerous vegetation indices, with Normalised Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Soil-adjusted Vegetation Index (SAVI) being the most popular ones. We are expecting that Serbian companies will also use this opportunity to develop industrial solutions based on Sentinel data and come out to the global market with their innovations.

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Sentinel Data Hub

Big data analytics is based on heterogeneous data sources coming at different velocity and at a different resolution. Besides satellite images, BioSense’s AI group uses probes for soil electrical conductivity, handheld devices and information coming from agricultural machinery. Electrical conductivity of the soil is an excellent indicator of soil texture, compaction and chemical content and these parameters are scanned at various depths, depending on the setup and the plants of interest. Elevation maps are not less important, as they determine the flow of nutrients and often correspond to the yield, while the handheld devices, such as the BioSense’s Plant-O-Meter, are allowing for continuous growth monitoring.

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<img class="alignnone wp-image-1486" src="https://api.biosens.rs/wp-content/uploads/2021/06/46-212x300.jpg" alt="" width="220" height="311" /><img class="alignnone wp-image-2435" src="https://api.biosens.rs/wp-content/uploads/2021/06/prostorna-212x300.jpg" alt="" width="220" height="311" />

<img class="alignnone wp-image-1489" src="https://api.biosens.rs/wp-content/uploads/2021/06/48-212x300.jpg" alt="" width="220" height="311" /> <img class="alignnone wp-image-1490" src="https://api.biosens.rs/wp-content/uploads/2021/06/9-212x300.jpg" alt="" width="220" height="311" />

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Using the techniques of data fusion, heterogeneous data are aggregated into a single dataset and used for the delineation of management zones. Zone delineation is done by applying clusterization algorithms on data, either in normalised or weighted form, depending on the relative importance of input features. These management zones have different properties between one another, but soil can be considered homogeneous within each of them. This allows for issuing recommendations concerning agricultural production separately for each zone, depending on its specifics. Such localised decision-making is the essence of the precision agriculture and it is also a necessary first step in determining the optimal sensor locations, which maximise their effectiveness.

Geospatial data analytics

The goal of BioSense’s AI Group is to get a comprehensive and accurate overview of biosystems, make phenotyping and plant breeding more efficient, understand molecular biology better and offer optimal and automatic decision-making to the farmer. Our research starts with the problem and requires innovative application of state-of-the-art algorithms and development of the novel ones. Machine learning algorithms extensively used in BioSense applications include Random Forest, SVM, Decision Trees, Ridge Regression, Spectral Clustering and many others including special family of machine learning algorithms- Deep Learning, and where the complexity of the problem goes beyond the available algorithms, BioSense researchers develop the novel ones.

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Example of novel algorithm is include weighted histograms regression (WHR). WHR is based on a voting mechanism, where training samples are voting for the output value of a test sample. The votes are weighted according to the similarity of features and used to form a histogram that essentially represents the PDF of the output, while the expectation of the PDF is essentially the predicted value. This algorithm proved very useful for yield prediction, where it outperformed random forest, SVM and artificial neural networks.

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<img class="alignnone wp-image-1478 size-full" src="https://api.biosens.rs/wp-content/uploads/2021/06/42.png" alt="" width="503" height="504" />

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Another novel algorithm is integrative clustering based on Nonnegative matrix factorization. Combining results of individual clusterings together into an ensemble leverages evidence accumulation in order to improve the results of clustering. Individual clustering results are merged into a joint cluster membership matrix that is further factorized into matrices of encodings and basis. Algorithm can integrate clusterings stemming from different data sets, different data preprocessing steps or different subsamples of features or objects.

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This algorithm proved very useful for functional genomics. Proposed approach based on nonnegative matrix factorization can fuse diverse data sources and infer gene clusters with high functional enrichment and improved gene coverage.

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Machine Learning

agROBOfood- Business-Oriented Support to the European Robotics and Agri-food Sector, towards a network of Digital Innovation Hubs in Robotics

Centar za inovacije i razvoj poslovanja

Centar za senzorske tehnologije

Cilj projekta: AgROBOfood projekat posvećen je ubrzanju digitalne transformacije Evropskog poljoprivredno-prehrambenog sektora kroz usvajanje tehnologija iz oblasti robotike.
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O projektu: AgROBOfood će konsolidovati, proširiti i ojačati postojeći ekosistem osnivanjem održive mreže digitalnih-inovacionih habova &#8211; DIH-ova. Aktivnosti će pospešiti usvajanje robotičkih rešenja od strane poljoprivredno-prehrambenog sektora što je ogroman izazov koji zahteva inkluzivni pristup uključujući sve relevantne Evropske igrače. AgROBOfood konzorcijum se sastoji od 39 partnera, koje predvodi univerzitet i istraživački centar Vageningen, kao i drugi ključni partneri prethodnih relevantnih projekata &#8211; IoF2020, ROBOTT-NET, PicknPack i I4MS, da bi se mogao iskoristiti ekosistem koji je uspostavljen u tim projektima. Središte projekta čine inovacioni eksperimenti (IE-ovi), organizovani i praćeni od strane DIH-ova. U svakom od 7 regionalnih klastera, početni inovacioni eksperimenti će demostrirati inovacije iz oblasti robotike u poljoprivredno-prehrambenom sektoru na način koji osigurava replikabilnost širom Evrope, veliko usvajanje i održivost mreže DIH-ova. AgROBOfood će raditi u skladu sa Evropskom zajednicom robotike, obezbeđujući sinergetske efekte sa inicijativama kao što je EU-Robotika. Na ovaj način će se maksimizirati povraćaj evropskih investicija, uključujući privatan kapital, u digitalnu trasformaciju poljoprivredno-prehrambenog sektora. Ključni instrument za postizanje ovog cilja je Industrijski savetodavni odbor. On će obezbediti strateške smernice i definisati prioritete za odabir rešenja koja će primiti finansiranje. Otvoreni konkursi za 8 miliona eura će privući dodatne inovacione eksperimente (12) i industrijske izazove (8). Oni će proširiti mrežu i obezbediti ogromne tehnološke napretke kao i uključivanje novih izazova poljoprivredno-prehrambenog sektora u portfolio usluga DIH-ova. Kroz svoju inkluzivnu strukturu i ambiciozne ciljeve, AgROBOfood teži da spoji čitav evropski ekosistem, tako da obezbedi efektivno usvajanje tehnologija u oblasti robotike u poljoprivredno-prehrambenom sektoru.
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<img decoding="async" loading="lazy" class="alignnone wp-image-690 " src="https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic-718x1024.png" alt="" width="700" height="998" srcset="https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic-718x1024.png 718w, https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic-210x300.png 210w, https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic-768x1095.png 768w, https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic-1078x1536.png 1078w, https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic-1437x2048.png 1437w, https://api.biosens.rs/wp-content/uploads/2021/06/agROBOfood_infographic.png 2000w" sizes="(max-width: 700px) 100vw, 700px" />

Nikica Marinković je diplomirani inženjer poljoprivrede – agroekonomskog smera, Univerziteta u Novom Sadu. Sticao je iskustva u raznim projektima – u poljoprivrednom sektoru, lokalnom ekonomskom razvoju i IT sektoru. Tokom profesionalne karijere osnovao je 3 startup preduzeća i proglašen je „Globalnim inovatorom“ od strane EXPO 2020 u Dubaiju za eko ambalažu od prirodne izolacije u obliku vune – prirodnu alternativu kontejnerima za transport hrane od stiropora. Takođe, ima iskustvo u poljoprivrednom sektoru malih i srednjih preduzeća kao direktor poljoprivrednog preduzeća specijalizovanog za proizvodnju voća. Usavršavao se u oblasti poljoprivrede u Italiji i Izraelu, posebno zainteresovan za socijalno preduzetništvo sa fokusom na hranu i lanac snabdevanja.

Branislava Davidović je stekla diplomu diplomiranog pedagoga na Filozofskom fakultetu, Univerzitet u Novom Sadu, Srbija. Prethodno je radila za privatne kompanije u različitim privrednim granama kao administrator a kasnije i kao referent za komercijalne i finansijske poslove. Nakon toga radila je za NVO. Tokom desetogodišnjeg rada u tom sektoru imala je priliku da unapredi svoje veštine i stekne iskustvo u pisanju predloga i implementaciji projekata, administraciji i finansijskom upravljanju, kao i pripremi finansijskih izveštaja. Projekti na kojima je radila bili su podržani i finansirani od strane Gradskih uprava Grada Novog Sada i Ministarstava Republike Srbije. U novembru 2022. Branislava se pridružila Biosens timu i trenutno radi kao asistent za upravljanje projektima u Centru za inovacije i razvoj poslovanja na Biosens Institutu. Aktivno je uključena u projektu agROBOfood.

Kristina Petrović je projektni menadžer u Centru za biosisteme u Institutu BioSens. Doktorirala je na Poljoprivrednom fakultetu Univerziteta u Beogradu 2013. godine na temu karakterizacije fitopatogenih gljiva prouzrokovača kompleksa oboljenja na soji. Kristina Petrović ima iskustva u različitim metodama karakterizacije oboljenja na soji. Njena istraživanja su u vezi sa iznalaženjem otpornosti soje prema prouzrokovačima bolesti što je izuzetno važno u poljoprivredi, prehrambenom sektoru i zaštiti životne sredine. Tokom 2010. i 2011. godine, boravila je u Centro di Ricerca per la Patologia Vegetale (CRA-PAV) u Rimu, Italija, na stručnom usavršavanju iz oblasti molekularne karakterizacije fitopatogenih gljiva, a postdoktorsko usavršavanje je obavila u Univerzitetu Južne Dakote, Brukings, SAD, tokom 2017. i 2018. godine. Učestvovala je na nekoliko nacionalnih i međunarodnih projekata, a bila je i koordinator radnog paketa u okviru evropskog ECOBREED projekta H2020. Kristina Petrović je autor ili koautor 90 naučnih radova u međunarodnim i domaćim časopisima, zbornicima radova sa međunarodnih i domaćih skupova, kao i patenta. Član je Upravnog odbora Evropske asocijacije za leguminoze, The American Phytopathological Society, The Australasian Plant Pathology Society i Društva za zaštitu bilja Srbije.

Goran Kitić je zaposlen na poziciji Rukovodioca centra za senzorske tehnologije na Institutu BioSens. Doktorirao je na Fakultetu tehničkih nauka, na Univerzitetu u Novom Sadu 2016. godine na temu mikrotalasnih senzora vlažnosti zemljišta. Goran Kitić ima iskustva u oblastima raznih tehnologija fabrikacije (LTCC, debeloslojna i tankoslojna tehnologija, mikrofabrikacija, PCB, wire bonding, mašinska obrada i 3D štampa) i metoda karakterizacije (elektronska mikroskopija, EDS spektoroskopija, UV/Vis spektroskopija, optička profilometrija, električna merenja). Njegova istraživanja su u vezi sa razvojem senzora koji svoju primenu imaju u poljoprivredi, prehrambenom sektoru i zaštiti životne sredine. Neki od razvijenih prototipa senzora uključuju multispektralni senzor za utvrđivanje statusa biljaka, senzor vlažnosti zemljišta, uređaj za rano otkrivanje mastitisa, detektor nitrata u vodi. Pored navedenog, u velikoj meri je uključen u razvoj robotskog sistema za uzorkovanje i analizu zemljišta. Njegovo istraživanje je publikovano u 7 međunarodnih časopisa, i brojnim radovima objavljenim na međunarodnim konferencijama. Tokom svoje karijere, učestvovao je u 13 međunarodnih i nacionalnih projekata.

Snežana Đurić, viši naučni saradnik, je doktorirala na Fakultetu tehničkih nauka, Univerzitet u Novom Sadu, Energetika, elektronika i telekomunikacije (Elektronika) 2013. godine. Oblasti interesovanja su bioelektronski sistemi, senzori, skladištenje i prikupljanje energije, induktivni sistemi i komponente.

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Slobodan Birgermajer je naučni saradnik u Centru za Senzorske Tehnologije pri Institutu BioSens. Doktorat iz mikrotalasne elektronike odbranio je 2019. godine na Fakultetu Tehničkoih Nauka, Univerziteta u Novom Sadu. Trenutno radi na razvoju i primeni senzora u poljprivredi, prehrambenoj industriji i monitoringu životne sredine, i aktivno je uključena na više međunarodnih projekata iz poziva H2020, kao što su ANTARES, SHEALTY, IPANEMA, i drugi. Takođe, domen istraživanja obuhvata razvoj i fabrikaciju mikrotalasnih pasivnih kola, fotonskih kristala, mikrofludinih senzora, kao i 3D i 4D tehnologiju štampe.

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Mina Mirović je zaposlena kao mlađi istraživač na BioSense Institutu. Osnovne studije iz oblasti mehatronike završila na Univerzitetu u Novom Sadu a Master studije iz oblasti mehatronike, robotike i embeded sistema završila je na London South Bank Univerzitetu.

Jovana Stanojev je istraživač saradnik i student doktorskih studija na Tehnološkom fakultetu u Novom Sadu, na Univerzitetu u Novom Sadu. Studirala je inženjerstvo materijala i trenutno završava svoju doktorsku disertaciju. Tema njene doktorske disertacije je "Razvoj nehlađenog infracrvenog detektora na bazi olovo selenida". Njeno istraživanje se fokusira na razvoj novih materijala za senzore, nanomaterijala i nanomembrana, mikrofluidiku, uzgajanje ćelijskih kultura i razvoj platformi organ-na-čipu.

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Damir Krklješ radi kao viši istraživač na institutu BioSense. Doktorirao je na Univerzitetu u Novom Sadu, Fakultet tehničkih nauka, Novi Sad, Srbija, 2016. Radio je kao istraživač i asistent u nastavi na Fakultetu tehničkih nauka, predajući elektroniku, senzore i aktuatore i mehatroniku. Za to vreme učestvovao je u mnogim nacionalnim i međunarodnim projektima, gde su mu glavne teme istraživanja bile robotika (senzorisana hvataljka sa dva stepena slobode. Senzorisano robotsko stopalo za ZMP-metenja), senzori sile (optički i otpornici osetljivi na silu) i kapacitivni senzori ugla i ugaone brzine, na bazi štampane elektronike na fleksibilnim podlogama. Počevši od 2013. prelazi u industriju, gde je radio za nekoliko kompanija, uglavnom u oblasti dizajnerskih usluga za vodeće svetske industrijske partnere. Bio je angažovan i kao inženjer i kao šef odeljenja. U tom periodu bio je uključen u razvoj industrijskih proizvoda koji uključuju vrhunske LED rasvete, digitalno kontrolisane pretvarače snage, sofisticirane uređaje za nadzor pumpi, pretvarače snage itd. Od 2019 radi na BioSens institutu. Damir Krklješ objavio je preko 30 časopisa i konferencijskih radova.

Csaba Petes je 2017. godine završio Master akademske studije na Univerzitetu u Novom Sadu, na Fakultetu tehničkih nauka, smer mikroprocesorski sistemi i algoritmi. Tema njegovog maser rada je bilo daljinsko upravljanje pokretnih vozila pomoću DTMF kodova i video signala na velike i male daljine. Osnovne akademske studije završio je 2014. godine na Univerzitetu u Novom Sadu, na Fakultetu tehničkih nauka, smer mikroračunarska elektronika, sa temom diplomskog rada : Razvoj i primena programa „Paint“ na embeded sistemu.
U među vremenu (septembar 2013) osnovao je sopstvenu kompaniju, konsultantsku agenciju „Starprofit“ koja je zastupala „Guttler GmbH“ u Srbiji i druge strane kompanije na srpskom tržištu, uglavnom u poljoprivrednom poslovanju. Paralelno radi kao menadžer prodaje i kao profesor stručnih predmeta u Elektrotehničkoj skoli „Mihajlo Pupin“ u Novom Sadu i u Tehničkoj školi u Bečeju od oktobra 2014. do septembra 2017. godine.
Od maja 2018. godine radi na Institutu Biosense, na embeded softveru i robotskim sistemima. Radi na više projekata (Antares, MIMA, AgroboFood, WaQuMoS), prvenstveno na razvoju analogne i digitalne elektronike za sistem očitavanja, na dizajniranju izgleda PCB-a, realizaciji prototipa PCB-a, podržavajući celokupan dizajn robota, integraciju i obradu signala. Kontakt adresa: petes.csaba@gmail.com ili chaba@biosense.rs

Milijana Vujasinović je rukovodilac Centra za razvoj proizvoda. Ima višegodišnje iskustvo u razvoju i implementaciju softverskih rešenje. U razvoju softverskih rešenja učestvovala je u početku kao programer i biznis analitičar, a kasnije i kao projektant rešenja i menadžer proizvoda. Bogato iskustvo je stekla radeći kao ERP konsultant i menadžer projekata u implementacijama softverskih rešenja u različitim privrednim granama – poljoprivrednoj,veleprodaji i maloprodaji, prehrambenoj industriju, tekstilnoj industriju, metalurgiji, industriji alata i kablova, građevinskoj industriju, uzlužnoj delatnost kao i u javnim preduzećima. Sertifikovani je SAP FI i SAP Project Manager. Više od 3 godine je upravljala PMO (Project Managment Office), odeljenjem koji kontroliše i unapređuje proces upravljanje projektima.

Maša Mimica radi kao projektni menadžer u Institutu Biosens na poslovima H2020 finansijskog menadžement ali i kao projektni menadžer podprojekata odabranih od strane Instituta. Ima bogato iskustvo iz finansijskog izveštavanja na projektnom nivou sa potfoliom od 17M€ i sa dokazanim iskustvom u planiranju, izveštavanju i analizi poslovnih potreba i drugim finansijskim aspektima Instituta. Maša kao deo Centra za inovacije i razvoj poslovanja sarađuje sa drugim odeljenjima u donošenju strateških odluka i rešavanju operativnih izazova
Paralelno s tim, Maša radi kao menadžer podprojekata finansiranih kaskadno, ranije u FP7, a sada u programu H2020. Kroz ovu vrstu poslova, stekla je veliko iskustvo u programima inovacija i akceleracije malih i srednjih preduzeća. Kroz projekte na kojima radi došlo je do pozicioniranja na tržištu i rasta više od 150 MSP, kako IT tako i poljoprivrednog sektora.
Maša ima iskustvo rada u multinacionalnom okruženju, gde je rad sa različitim stranama u raznim industrijama doprineo razvoju njenih poslovnih i međuljudskih veština.

Isidora Stojačić radi kao menadžer na projektima u Centru za inovacije i razvoj poslovanja Instituta BioSens. Diplomirala je na Univerzitetu u Novom Sadu, na Ekonomskom fakultetu, završila master na Univerzitetu Cattolica del Sacro Cuore, Fakultetu za poljoprivredu kao i na Tehničkom univerzitetu u Minhenu, na Fakultetu prirodnih nauka. Isidora ima iskustva u upravljanju projektima, istraživanju i pisanju predloga projekata. Tokom svoje karijere, imala je dodira sa različitim temama projekata, uglavnom povezanim sa odgovornim istraživanjima i inovacijama (RRI), zajedničkim društvenim stvaranjem vrednosti, socijalnim dizajnom i implementacijom istog, tržišnim i poslovnim strategijama i razvojnim projektima. Bila je uključena u programe Horizon2020, ERASMUS + i srpske nacionalne projekte.

Dragana Petković je menadžerka projekata na Institutu BioSens u Novom Sadu i koordinatorka BioSens Akceleratora za agri-tech startape u ranoj fazi. Diplomirala je na Fakultetu političkih nauka u Beogradu. Jedan je od osnivača Coworking Asocijacije Srbije, osnivač i nekadašnja izvršna direktorka Startita, vodeće organizacije za podršku IT i startap zajednici u Srbiji. Radila je kao nezavisna konsultantkinja na brojim projektima za razvoj startap ekosistema i preduzetništva, u okviru GIZ-a i Luke Beograd. Ima višegodišnje iskustvo u mentorstvu i konsaltingu za startape u različitim industrijama.

Željana Grbović je istraživač i student doktorskih studija na departmanu Energetika, elektronika i telekomunikacije na Fakultetu tehničkih nauka, Univerzitet u Novom Sadu. Njena oblast interesovanja obuhvata primenu mašinskog učenja u poljoprivredi. Algoritmima veštačke inteligencije je počela da se bavi 2016. godine kada je njen tim rangiran u TOP5 u konkurenciji od 52 tima na prestižnom takmičenju u obradi signala, SP Cup koji organizuje IEEE. Završila je master studije 2017. godine na temi detektovanja klasova pšenice u termalnim slikama korišćenjem dubokih konvolucionih neuronskih mreža. Istraživanje o pšenici je proširila i na ranu predikciju prinosa, na osnovu slika sa mobilnog telefona i drona, za šta je dobila finansiranje od Inovacionog Fonda, za Dokaz Koncepta. Gostujući je istraživač na Univerzitetu u Vageningenu (Wageningen University and Research (WUR)), u grupi za Kompijutersku viziju i robotiku u poljoprivredi. Učestvovala je u industrijskom projektu WUR-a i kompanije GreenYard, pod nazivom Humistatus, za predikciju širenja patogenih oboljenja na paradajizu, na osnovu hiperspektralnih slika. Glavni domen istraživanja je transfer dubokog učenja u oblasti procene prinosa, kvaliteta i bezbednosti useva u poljoprivredi. Predvodila je tim koji je osvojio nagradu na studentskom univerzitetskom takmičenju „Space4Women“ i koji je učestvovao u finalu svetskog „Alibaba Get Global Challenge“ takmičenja. Aktivni učesnik je na nekoliko Horizon 2020 projekata, uključujući ANTARES, Cybele, Dragon (Menadžer diseminacije) i AgROBOfood, kao i projekte sa kompanijama.

Predrag Matavulj je doktorand informatike sa znanjem u teoriji verovatnoće i statistici, numeričkoj optimizaciji, mašinskom učenju i neuronskim mrežama, od kojih je većinu stekao tokom osnovnih studija matematike i master studija nauke o podacima na PMF-u Novi Sad. Tokom rada na master tezi, Predrag je u martu 2018. godine započeo svoj rad kao mlađi istraživač na Institutu BioSense, gde je koristio tehnike dubokog učenja za identifikaciju i klasifikaciju bioaerosola. Od novembra 2018. Predrag predaje duboko učenje kao asistent u nastavi odgovoran za master kurs na smeru Data Science na PMF-u. Uključen je u nekoliko nacionalnih i međunarodnih projekata, uključujući Antares, Dragon, agROBOfood, PROMIS.

Dr Oskar Marko je rukovodilac Centra za informacione tehnologije i pomoćnik direktora za inovacije i saradnju sa privredom. Njegovo istraživanje usmereno je ka primeni naprednih metoda mašinskog učenja i evolutivnih algoritama u poljoprivredi. Treću godinu osnovnih studija je pohađao je na “Siti univerzitetu” u Londonu, gde je odbranio diplomski rad u domenu obrade signala. Vodio je tim BioSensa koji je razvio nove algoritme iz oblasti obrade velikih podataka koje su za cilj imale predikciju prinosa, distribuciju semena i optimizaciju strategije setve, koje su Institutu osigurale prvo mesto na Sindžentinom “Izazovu za useve” i CGIAR-ovom “Inspirišućem izazovu”. Aktivno je uključen u mnoge projekte iz poziva Horizont 2020, među kojima su Antares, Cybele, Dragon i Flexirobots, kao i u projekte sa kompanijama poput Krivaje, MK Agri, Delte i drugih poljoprivrednih kompanija i osiguravajućih kuća.

Mirjana Radulović je istraživač-pripravnik na Institutu Biosens čija interesovanja su okrenuta ka daljinskoj detekciji, geoinformatici, upravljanju vodnim resursima, poljoprivredi i životnoj sredini. Ona je trenutno student doktorskih studija geonauka na Prirodno-matematičkom fakultetu, Univerzitetu u Novom Sadu gde je takođe stekla diplomu osnovnih (2017) i master studija (2018) u oblasti hidrologije i geoinformatike. Tokom master studija pet meseci provela je na Univerzitetu Palacký u Olomoucu (Republika Češka), gde je studirala kao stipendista Erasmus + programa razmene. U martu 2019. godine pridružuje se Institutu Biosens gde radi na primeni geografskih informacionih sistema i tehnologija daljinske detekcije za praćenje navodnjavanih površina, suše, stanja useva, klasifikaciju iskoristivosti zemljišta, praćenje podzemnih voda itd. Učestvuje na nekoliko nacionalnih i internacionalnih projekata vezanih za navedene teme. Bila je autor i koautor na nekoliko radova i prisustvovala je na nekoliko naučnih konferencija.

Miloš Pandžić je istraživač pripravnik čije interesovanje pokriva nekoliko istaživačkih oblasti: osmatranje Zemlje, daljinsku detekciju, obradu slike i analitiku podataka. Trenutno je student doktorskih studija odseka za Geodeziju i geoinformatiku na Građevinskom fakultetu, Univerziteta u Beogradu, gde je takođe završio i osnovne i master akademske studije. U 2015. godini dobio je stipendiju vlade Austrije (OeAD) i proveo 4 meseca na Tehničkom univerzitetu u Beču gde je analizirao geometrijski kvalitet Sentinel-2 satelitskih multispektralnih snimaka. Iz ovog istraživanja je proizašao i Milošev master rad. Nakon završetka studija, radio je u Finskom geoprostornom istraživačkom institutu (Finnish Geospatial Research Institute - FGI) na više projekata finansiranih od strane Finske Akademije i Evropske svemirske agencije. Tu je radio na segmentaciji i detekciji promena na satelitskim slikama za potrebe poljoprivrede, urbanizma i šumarstva. U 2018. godini pridružio se Institutu BioSens gde radi na fuziji podataka optičkih i radarskih slika za procenu prinosa, klasifikaciju useva, praćenje razvoja useva, itd. Učestvuje u realizaciji nekoliko nacionalnih i internacionalnih projekata uključujući Horizon 2020 projekte Antares, Cybele, Dragon, PARSEC i agROBOfood.

Dr Marko Panić je naučni saradnik u oblasti tehnološko-tehničkih nauka – informacionih tehnologija na institutu BioSens. Tema doktorata mu je vezana za razvoj algoritama za ubrzanu rekonstrukciju slika iz nepotunih merenja korišćenjem retke reprezentacije signala I statističkih Markovljevih slučajnih modela Njegov pravac istraživanja obuhvata statističko modelovanje multidimenzionalnih podataka dobijenih sa različitih senzora. Trenutno radi na analizi I obradi slika dobijenih sa hiperspektralnih I multispektralnih kamera korišćenjenem naprednih metoda mašinskog učenja sa primenom u proceni kvaliteta voća I povrća. Kao član tima BioSens ucestvovao je na Sindžentinom takmičenju “Izazovu za useve” koje rezltiralo osvajanjem prvog mesta. Aktivno je uključen u mnoge projekte iz poziva Horizont 2020, među kojima su Antares, Cybele, Dragon i Flexirobots, kao i u projekte sa kompanijama poput Krivaje, MK Agri i Delta Agrar.

Dragana Blagojević je završila osnovne (2017) i master (2018) akademske studije smer geograf-geoinformatičar na Departmanu za geografiju, turizam i hotelijerstvo na Prirodno-matematičkom fakultetu u Novom Sadu. Njena istraživanja za završne radove su obuhvatala upotrebu geografskih informacionih sistema u analizi hidroloških i geomorfoloških procesa u prirodi. Na istom fakultetu, u oktobru 2018. godine upisuje doktorske studije, smer – Geonauke. Letnji semestar master studija provela je u Češkoj na Departmanu za Geoinformatiku na Palacki Univerzitetu u Olomoucu kao stipendista Erasmus+ programa razmene studenata. U januaru 2018. godine počinje da radi na Institutu BioSens gde je zaposlena kao istraživač-pripravnik u okviru Centra za informacione tehnologije. Njeni domeni istraživanja su daljinska detekcija, precizna poljoprivreda, monitoring i mapiranje prinosa, kao i analiza podataka dobijenih na terenu. Cilj njenog istraživanja je integracija ovih tehnika kako bi se dobila kompletna i precizna informacija o stanju poljoprivredne parcele, useva, fizičkih karakteristika terena i zemljišta.

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Branislav Pejak je student doktorskih studija Elektrotehničkog i kompjuterskog inženjerstva na Fakultetu tehničkih nauka, Univerziteta Novi Sad, na kojem je takođe završio osnovne (2017) i master (2018) studije u oblsti Biomedicinskog inženjerstva. Tokom osnovnih i master studija bio je stipendista Ministarstva obrazovanja, nauke i tehnološkog razvoja, Republike Srbije. Od marta 2018. godine zaposlen je u Centru za informacione tehnologije, Instituta BioSens, na poziciji mlađeg istraživača. Tema njegovog istraživanja je analiza podataka sa satelitskih snimaka. Trenutno se bavi razvojem GAN algoritama mašinskog učenja za klasifikaciju i predikciju prinosa na bazi multispektralnih satelitskih snimaka. Aktivno je uključen u mnoge projekte sa poziva Horizont 2020, među kojima su Antares, Cybele, Dragon i AgRoboFood koji imaju za cilj upotrebu informaciono-komunikacionih tehnologija u poljoprivredi poput kreiranja mapa za selektivno uzorkovanje i đubrenje zemljišta, detekciju navodnjavanih površina, procenu prinosa i proteinskog sastava useva.

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Ovaj projekat je finansiran od strane Evropske Unije, iz programa za Istraživanje i Inovacije-Horizont 2020, pod sporazumom o grantu broj 825395.


Horizont 2020

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BioSens Institut (Istraživačko - razvojni institut za informacione tehnologije biosistema) je vodeći srpski Digitalni Inovacioni Hab (DIH) koji je fokusiran na okupljanje različitih interesnih grupa iz industrije, naučne oblasti, preduzetničke zajednice i javnosti. Kao takav, BioSens je jedinstveni šalter (One-Stop-Shop) koji pruža usluge u domenu informacionih i komunikacionih tehnologija u poljoprivredi.

Obzirom da je ekosistem DIHova u Srbiji i regionu još uvek u početnoj fazi razvoja, BioSens aktivno radi na ostvarenju svog cilja – približavanju digitalnih rešenja tržištu, korisnicima, poljoprivrednicima, stručnoj i široj zajednici. Tri vrste usluga su u osnovi BioSense DIH-a: poslovne, tehničke i usluge umrežavanja. Osim toga, kontinuirano stručno usavršavanje korisnika i razvoj neophodnoh veština su krovne aktivnosti DIH-a. Korisnicima naših usluga na raspolaganju je podršku u procesu:

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- razvoja tehničkih rešenja - u vidu stručnih, tehničkih, poslovnih i finansijskih saveta (putem <a href="/collaborate/biosens-akcelerator?id=1829">BioSens akceleratora</a>)
- umrežavanja sa relevantnim zajednicama i partnerima iz ekosistema
- testiranja rešenja putem<a href="/collaborate/laboratorija?id=76"> žive labaratorije PA4ALL</a>

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Usluge se realizuju putem brojnih projektnih i komercijalnih aktivnosti DIH-a. Inovacije koje podržava BioSens aktivno koriste poljoprivrednici, savetodavne službe, preduzetnici, srednje stručne škole, profesori i studenti. Multidisciplinarni pristup omogućava sveobuhvatno razumevanje inovacija u svim fazama razvoja, po čemu je DIH jedinstven.

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Aktivnosti i dostignuća BioSense DIH-a prepoznati su kako u Srbiji tako i u svetu. Od 2015. godine BioSens je uključen u neke od najvećih evropskih DIH projekata, kao što su IoF2020, SmartAgriHubs, agROBOfood i DIATOMIC. BioSens DIH je takođe deo inicijative <a href="https://smartanythingeverywhere.eu/">Smart Anything Anywhere</a>, putem koje pruža srtučnu podršku malim i srednjim preduzećima, kao i podršku u pristupu potencijalnim izvorima finansiranja. Institut sarađuje sa velikim multinacionalnim korporativnim akterima iz različitih industrija poput industrije sofrvera, kompjuterskih igara, osiguranja, zatim nacionalnim telima kao što su Ministarstvo poljoprivrede, šumarstva i vodoprivrede, Kabinetom premijera, kao i sa građanima, poljoprivrednicima, obrazovnim i naučnim institucijama, drugim DIH-ovima, političkim akterima, itd. Kroz ove projekte i aktivnosti, BioSens aktivno doprinosi digitalizaciji domaćeg, ali i evropskog tržišta na kojem je uveliko prepoznat kao relevantan akter u domenu razvoja tehnoloških rešenje u poljoprivredi.

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Ukoliko ste zainteresovani da saznate više o BioSens DIH-u ili želite da čujete više o uslugama koje nudimo možete nas kontaktirati na Trajković [na] <a href="/employees/milica-trajkovic/">biosense.rs.</a>

Digitalni Inovacioni Habovi

Lansirajte svoju AgTech ideju!


BioSens akcelerator je intenzivan, tromesečni program namenjen AgTech startapima u ranoj fazi i predstavlja snažan most između nauke i biznisa. Program omogučava startapima da rastu, ubrzaju svoje putovanje od početne AgTech ideje do biznisa, i reše ključne izazove u poljoprivredno-prehrambenom sektoru. BioSens akcelerator je jedini takve vrste u Srbiji koji pruža podršku domaćim i regionalnim IT preduzetnicima usredsređenim na stvaranje inovativnih i revolucionarnih digitalnih rešenja za poljoprivredu.

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Prvi BioSens akcelerator počeo je u oktobru 2019. godine i tokom tri meseca koja su bila ispunjena interaktivnim radionicama i specijalnim treninzima, 8 timova savladalo je nekoliko veština: kako razviti poslovnu ideju, definisati poslovni model, identifikovati potrebe budućih korisnika i sprovesti detaljnu analizu tržišta i konkurencije. Zahvaljujući vrhunskoj tehničkoj i poslovnoj podršci, kao i smernicama prominentnih stručnjaka- mentora, startapi su svoju početnu ideju podgili na viši nivo. Nakon veoma uspešnog prvog BioSens akceleratora, Institut BioSens nastavlja da podržava preduzetnike. U realizaciji BioSens akceleratora 2020., Institut je udružio snage sa Evropskim fondom za Jugoistočnu Evropu i najboljim B2B akceleratorom u Evropi, Startup Wise Guys.

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Pored tehničke, poslovne i mentorske podrške, BioSens akcelerator omogućio je timovima i da se upoznaju sa strategijom prikupljanje sredstava, a startapi koji su učestvovali u programu prikupili su 140 hiljada evra tokom šest meseci. Ideja BioSens akceleratora jeste da podstakne preduzetnički mentalitet u našoj zemlji, a time i ekonomski razvoj, kao i da motiviše regionalne IT preduzetnike da hrabro stvaraju svoje proizvode.

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Saznajte više: <a href="http://accelerator.biosense.rs/">BioSens akcelerator</a>

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<img class="alignnone wp-image-1882 size-large" src="https://api.biosens.rs/wp-content/uploads/2021/07/The-first-BioSense-accelerator-graduates-2019-1-1024x683.jpg" alt="" width="1024" height="683" />

BioSens akcelerator

Upotreba robotike u poljoprivredi je oblast u nauci koja se sve više razvija i sa novim rešenjima dospeva na tržište. Značajan napredak u ovoj oblasti uzrokovan je nedostatkom radne snage, porastom troškova proizvodnje kao i zamorom i repetitivnošću koje određeni zadaci nose sa sobom. BioSens koristi robote kao platforme koji se kreću i prikupljaju informacije o usevu. Ove platforme su opremljene senzorima koji su komercijalno dostupni i senzorima koje je razvila grupa za dizajn senzora Instituta BioSens.

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Najveći projekat na kom je institut radio je vezan za analize tla na terenu. Predloženi sistem se kreće kroz polje i vrši uzorkovanje zemljišta i analizu parametara (makronutrijenti, mikronutrijenti, pH, elektroprovodljivost) kao i georeferenciranje rezultata analize. Kompletan proces je autonoman jer je moguće unapred definisati rutu koju će robotska platforma preći na parceli koristeći GPS koordinate i 3D Real-Time-LIDAR sistem za rekonstrukciju okruženja i izbegavanje mogućih prepreka. Kao rezultat analize, generišu se višeslojne mape gde svaki sloj predstavlja jedan od parametara dobijenih predloženim sistemom. Poljoprivrednik će pomoću ovih mapa moći da donese pravu odluku, poboljša proizvodnju i u potpunosti iskoristi preciznu poljoprivredu u pogledu efikasnosti, povećanja prinosa i održivosti poljoprivredne proizvodnje.

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Robotika

Na Institutu BioSens koristimo slike kvadkoptera DJI Inspire 1 kako bismo dobili bolji uvid u stanje useva i preciznije planirali i upravljali agroekološkim aktivnostima. Ova tehnologija omogućava prikupljanje podataka visoke rezolucije ispod nivoa oblaka sa mnogo više detalja nego što se može videti u satelitskim snimcima. Skup podataka uključuje slike iz vidljivog dela spektra kao i slike dobijene modifikovanom NDVI kamerom. Takođe koristimo i Flir termalnu kameru za merenje temperature na velikim površinama u hetoregenim staništima. Bespilotne letelice su jednostavne za upotrebu, jer se većina mapiranja terena i prikupljanja podataka sada sprovodi autonomno, prema zadatim granicama terena uz pomoć aplikacija za planiranje leta.

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Za preklapanje slika koristimo softvere Pix4D i AgisoftPhotoscan kako bismo generisali ortomozaike, mape vegetacionih indeksa i digitalne modele površine. Ove orto-mape su važni slojevi informacija i mogu se integrisati u GIS sisteme zajedno sa slojevima podataka dobijenih iz drugih izvora. Ovakvi skupovi podataka se zatim obrađuju i koriste za obuku naprednih algoritama mašinskog učenja.

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BioSens koristi bespilotne vazdušne sisteme za otkrivanje nedostatka hranljivih materija u biljkama, napada štetočina, prekomerne suše ili vlage kao i drugih faktora koji utiču na razvoj useva, kao i za povećanje efikasnosti pri donošenju odluka. Posebno su korisni za površine od nekoliko desetina hektara, poput voćnjaka i vinograda, jer skeniranje velikih ratarskih parcela zahteva mnogo vremena. Bespilotne letelice su se pokazale i kao efikasni alati za praćenje stanja ekosistema. Pokrivajući veća prostranstva, omogućavaju pristup informacijama o tipu staništa u kojem rastu i razvijaju se živi organizmi od insekata do sisara. Njihova upotreba dovela je do revolucionarnih otkrića na poljima prostorne ekologije i poljoprivrede, i omogućila nam dobijanje podataka visoke rezolucije za donošenje optimalnih odluka sa visokom preciznošću.

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NDVI map of sugar beet crop

Obrada slika sa dronova

BioSens je dom habu za Sentinel podatke i kao takav je korisnik proizvoda Kopernikus programa Evropske svemirske agencije (ESA). Pre lansiranja Sentinel satelita, naša istraživanja su se zasnivala na snimcima sa satelita Landsat 7 i 8, kao i RapidView-a, ali su danas primarno usmerena na podatke koji potiču sa Sentinel 1 i 2 misija. Slike sa Sentinela 2 sadrže 13 spektralnih kanala i dostupne su na svakih 5 dana u zavisnosti od oblačnosti, dok Sentinel 1 koji snima radarske slike omogućava praćenje čak i u slučaju oblačnosti. Na ovaj način omogućeno je kontinualno osmatranje površine Zemlje u visokoj rezoluciji uključujući praćenje poljoprivrednje proizvodnje kroz sve faze rasta biljaka.

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Od 2012. godine proizvodimo mape upotrebe zemljišta za Autonomnu Pokrajinu Vojvodinu, gde klasifikujemo zemljište u šume, vodene mase, urbane površine i različite tipove useva. Ovakve mape su nam omogućile da mapiramo životinjska staništa, posmatramo kako se menjaju tokom godina i ispratimo plodored na proizvodnim parcelama. Oslanjajući se na principe fuzije podataka, uspeli smo da dođemo do sub-pikselske rezolucije korišćenjem višestrukih izvora podataka sa heterogenim mrežama piksela. Druga grana našeg istraživanja se bavi prognozom prinosa useva. Na osnovu podataka sa terena dobijenih pomoću digitalnih knjiga polja, kraudsorsinga ili mapa prinosa, obučavamo napredne modele mašinskog učenja u cilju što bolje procene prinosa. Ovakvi modeli koriste više od 30 satelitskih vegetacionih indeksa koji uključuju domensko znanje o usevima, a njihova tačnost se povećava kako napredujemo kroz faze razvoja biljaka. Vegetacioni indeksi su takođe odlični pokazatelji procene štete jer neki od njih veoma dobro reaguju na pojavu prirodnih nepogoda poput suše, požara i izmrzavanja. Na ovaj način se osiguravajuća društva uključuju u partnerstvo sa Institutom, zajedno sa državnim oragnima, istraživačkim institucijama i poljoprivrednim proizvođačima koji naše rezultate koriste za optimalno donošenje odluka o navodnjavanu i distribuciji đubriva i pesticida.

Obrada satelitskih slika

Evropska svemirska agencija je kroz Kopernikus program lansirala plejadu Sentinel satelita. Sa svojih 7 milijardi evra ulaganja, Kopernikus je najambiciozniji poduhvat satelitskog snimanja Zemlje u istoriji svemirskih istraživanja, a podaci sa satelita su našli široku primenu u praćenju klimatskih promena, građevinarstvu, saobraćaju i reagovanju u kriznim situacijama poput zemljotresa i vremenskih nepogoda. Podaci generisani kroz ovaj projekat su besplatni i potpuno otvoreni za svakoga. Veruje se da će evropska privreda do 2030. generisati čak 30 milijardi evra kroz preduzeća čija delatnost se zasniva na obradi satelitskih slika. Zbog ovako velikog zamajca koji Kopernikus daje visokotehnološkim startapovima i velikim kompanijama, često se koristi izraz „Kopernikus ekonomija“.

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Godine 2017. Srbija je postala jedina zemlja koja kao pridruženi član EU ima širokopojasni pristup ESA-inim slikama. Hab za Sentinel podake koji je otvoren na Institutu BioSens dobija podatke sa satelita, a nakon toga se podaci obrađuju na serverima visokih performansi. Za samu diseminaciju satelitskih slika zadužen je softver zasnovan na Javi - DHuS (Dejta Hab Softver). DHuS je softver otvorenog koda koji obezbeđuje jednostavno veb okruženje za interaktivno otkrivanje i preuzimanje podataka, kao i odličan interfejs za programiranje aplikacija (API) koji korisnicima omogućava pristup podacima preko sopstvenih računarskih programa, skripti ili klijentskih aplikacija. Time se automatizuje preuzimanje u okviru njihovog radnog procesa, a sami snimci postaju dostupni zainteresovanim stranama iz svih krajeva sveta.

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ESA-ine satelitske slike se već uveliko koriste na Institutu, za dobijanje mapa setvene strukture, procenu prinosa i praćenje rasta i razvoja useva u čiju svrhu se koriste brojni vegetacioni indeksi od kojih su najpoznatiji „normalizovani diferencijalni vegetacioni indeks“ (NDVI), „unapređeni vegetacioni indeks“ (EVI), „indeks vegetacije prilagođen zemljištu“ (SAVI) i mnogi drugi. Očekujemo i da će srpska preduzeća iskoristiti ovu priliku, razviti industrijska rešenja na bazi Sentinel slika i sa svojim inovacijama izađi na svetsko tržište.

Hab za Sentinel podatke

Analitika velikih podataka se zasniva na obradi heterogenih izvora podataka, različitih rezolucija, koji se prikupljaju u nejednakim vremenskim intervalima. Osim satelitskih podataka, Grupa za veštačku inteligenciju Instituta BioSens prikuplja i koristi podatke dobijene pomoću elektromagnetne sonde koja meri električnu provodnost zemljišta, kao i brojne druge instrumente koji se montiraju na poljoprivredne mašine ili koriste iz ruke. Električna provodnost zemljišta je odličan indikator teksture zemljišta, njene kompaktnosti i hemijskog sastava. Ovi parametri mogu se odrediti na različitim dubinama u zavisnosti od potreba i interesovanja korisnika prema tipu biljaka. Mape elevacije terena nisu ništa manje važne s obziorm na to da određuju pravac i smer oticanja nutrijenata koji je u tesnoj sprezi sa prinosom, dok se ručni uređaji, poput Plant-O-Meter-a razvijenog od strane istraživača Instituta BioSens, uspešno koriste pri monitoringu rasta useva.

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<img class="alignnone wp-image-1486 " src="https://api.biosens.rs/wp-content/uploads/2021/06/46.jpg" alt="" width="220" height="312" /><img class="alignnone wp-image-2435" src="https://api.biosens.rs/wp-content/uploads/2021/06/prostorna-212x300.jpg" alt="" width="220" height="311" />

<img class="alignnone wp-image-1487" src="https://api.biosens.rs/wp-content/uploads/2021/06/47-212x300.jpg" alt="" width="220" height="311" /><img class="alignnone wp-image-1490" src="https://api.biosens.rs/wp-content/uploads/2021/06/9-212x300.jpg" alt="" width="220" height="311" />

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Korišćenjem tehnika fuzije podataka, heterogeni podaci se agregiraju u jedinstven skup koji se koristi za iscrtavanje, odnosno određivanje menadžment zona. Određivanje zona vrši se algoritmima klasterizacije bilo u normalnoj ili težinskoj formi, što zavisi od relativne važnosti ulaznih podataka. Ove menadžment zone međusobno imaju različite osobine, ali se u okviru jedne zone zemljište može posmatrati homogenim. To dalje omogućava davanje preporuka o poljoprivrednoj proizvodnji za svaku zonu ponaosob, u skladu sa njenim specifičnostima. Ovakav pristup donošenju odluka u okviru jedne parcele osnova je za preciznu poljoprivredu, a ujedno je i prvi korak pri određivanju optimalne lokacije za postavljanje senzora jer se na taj način maksimizuje njihova efikasnost.

Analitika prostornih podataka

Sa napretkom tehnologija za varijabilno tretiranje u pogledu sejanja, zalivanja, aplikacije đubriva, pesticida i herbicida, javila se i potreba za sistemima koji tačno, precizno i brzo mogu da odrede varijabilnost zemljišta i identifikuju zone unutar jedne parcele.

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Ovako složen zadatak rešavamo pomoću robotske platforme Agrobot Lala, koja je posebno prilagođena za poljoprivredne primene kao i za ugrađivanje senzora za analizu zemljišta i sistema za uzorkovanje. Predloženi sistem se kreće po parceli i radi uzorkovanje zemljišta i analizu parametara zemljišta kao i georeferenciranje rezultata merenja.

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Celokupan proces je autonoman pošto je moguće prethodno definisati rutu Agrobot Lale na parceli pomoću GPS koordinata i 3D Real-Time-LIDAR sistema.

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Kao rezultat sprovedenih analiza, kreiraju se višeslojne mape, na osnovu kojih poljoprivrednik će biti u mogućnosti da donese ispravne odluke, optimizuje svoju proizvodnju i u potpunosti iskoristi preciznu poljoprivredu u pogledu efikasnosti, prinosa i održivosti poljoprivredne proizvodnje.

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<img class="alignnone wp-image-1493 size-full" src="https://api.biosens.rs/wp-content/uploads/2021/06/51.jpg" alt="" width="672" height="422" />

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Projekti:

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agROBOfood: Business-Oriented Support to the European Robotics and Agri-food Sector, towards a network of Digital Innovation Hubs in Robotics, H2020-DT-2018-1

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Razvoj uređaja za merenje i mapiranje azota kao najvažnijeg parametra za održivu poljoprivredu, broj rešenja 114-451-2794/2016-03, Pokrajinski sekretarijat za visoko obrazovanje i naučnoistraživačku delatnost, Autonomna pokrajina Vojvodina, Republika Srbija.

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Agrobot za analizu zemljišta na terenu

Cilj BioSensove Grupe za veštačku inteligenciju je da obezbedi sveobuhvatan i precizan uvid u stanje biosistema, poveća efikasnost fenotipizacije i oplemenjivanja biljaka, ponudi bolje razumevanje molekularne biologije i pomogne poljoprivrednicima kroz optimalno i automatsko donešenje odluka. Naše istraživanje počinje od problema i zahteva inovativnu primenu i razvoj algoritama koji su poslednja reč nauke. Algoritmi mašinskog učenja koji se najčešće koriste za probleme kojima se BioSens bavi su stabla odluke, vektori nosači, ridž regresija, spektralno klasterovanje i mnogi drugi, uključujući i posebnu porodicu algoritama mašinskog učenja – duboko učenje, a tamo gde složenost problema prevazilazi postojeće algoritme, istraživači sa Instituta razvijaju nove.

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Primer algoritma koji je razvijen na BioSens Institutu je algoritam regresije težinskim histogramima. Dati algoritam je zasnovan na mehanizmu glasanja, gde uzorci za obuku glasaju za izlaznu vrednost test uzorka. Svaki glas dobija određenu težinu u zavisnosti od sličnosti uzorka koji glasa i uzorka iz test skupa. Pomoću dobijenih glasova, formira se histogram koji de fakto predstavlja funkciju gustine verovatnoće (PDF) izlaza test uzorka, dok matematičko očekivanje PDF-a predstavlja predikovanu vrednost datog uzorka. Ovaj algoritam se pokazao veoma korisnim za problem predikcije prinosa, gde je nadmašio algoritme stabla odluke, vektora nosača i veštačkih neuronskih mreža.

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<img class="alignnone wp-image-1478 size-full" src="https://api.biosens.rs/wp-content/uploads/2021/06/42.png" alt="" width="503" height="504" />

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Još jedan inovativni algoritam koji je razvijen na Institutu BioSens je algoritam integrisane klasterizacije zasnovan na nenegativnoj faktorizaciji matrica. Kombinovanjem individualnih rezultata klasterovanja u ansambl, dokazi se akumuliraju u cilju poboljšanja rezultata klasterizacije.

Individualni rezultati klasteriziacije spojeni su u zajedničku matricu koja se zatim faktorizuje u matrice kodovanja i bazne vektore. Algoritam ima mogućnost da integriše klastere koji potiču iz različitih baza podataka, različitih nivoa predprocesiranja ili poseduju različite podskupove obeležja.
Ovaj algoritam se pokazao kao izuzetno koristan za funkcionalnu genomiku. Dati pristup, zanosvan na nenegativnoj faktorizaciji matrica poseduje mogućnost fuzije različitih izvora podataka i rezultuje klasterima gena sa povećanom funkcionalnošću i pokrivenošću gena.

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<img class="alignnone wp-image-1480 size-full" src="https://api.biosens.rs/wp-content/uploads/2021/06/43.png" alt="" width="1691" height="692" />

agROBOfood-Business-Oriented Support to the European Robotics and Agri-food Sector, towards a network of Digital Innovation Hubs in Robotics

Teme:

Ljudi:

Centri:

CIRP

CST