Hernandez, A.; Murcia, H.; Copot, C.; De Keyser, R. Towards the development of a smart flying sensor: Illustration in the field of precision agriculture. From the drone data, insights can be drawn regarding crop health, irrigation, spraying, planting, soil and field, plant counting and yield prediction, and much more. They store your settings and browsing preferences like language preferences so that you have a better and efficient experience on future visits to the website. Hungary's first smart agriculture lab is a first step in-field monitoring, digitization, and LoRaWAN network expansion. A system employing open hardware to allow the creation of a smart farming framework is presented in [, Smart farming has become a reality with the growth of the IoT and unmanned aerial vehicles. All rights reserved. Architecture designed for ultra-low power consumption. It can also consume off-farm data, such as market information and dealer availability, to enable informed decision-making post-harvest processes. Gao, X.; Shan, C.; Hu, C.; Niu, Z.; Liu, Z. The framework adopts the concept of a charging token, where upon completing a trip, UAVs receive tokens from the fog node. The Complete Guide to Smart Agriculture & Farming. The biggest challenge that farmers faced was the inability to manage field data. [, Min, E.; Long, J.; Liu, Q.; Cui, J.; Cai, Z.; Ma, J. Su-ids: A semi-supervised and unsupervised framework for network intrusion detection. In addition to this, smart farming, through the implementation of new technology in agriculture, makes it easier to trace anomalies in crop growth as well as livestock health. Visualize historical trends to make changes next season. On November 15, 2022 worlds population hit the 8 billion mark. The simulation model is parameterized with realistic values based on existing literature and real-world data. Skip to main content Parametric Search Shop Investors Blog mySemtech EN EN CN In order to be human-readable, please install an RSS reader. Less transport costs: human interventions only when needed. Monitoring soil moisture and trunk diameter in vineyards to control the amount of sugar in grapes and grapevine health. In this paper, a fog computing-based smart farming framework is proposed that utilizes UAVs to gather data from IoT sensors deployed in farms and offloads it at fog sites deployed at the network edge. articles published under an open access Creative Common CC BY license, any part of the article may be reused without Plant and soil microclimate monitoring with sensors specifically designed for agriculture. The overall sentiment is of caution. Bodkhe, U.; Tanwar, S.; Bhattacharya, P.; Kumar, N. Blockchain for precision irrigation: Opportunities and challenges. ; Ahmad, D.; Weltzien, C.; Yamin, M. Fundamental research on unmanned aerial vehicles to support precision agriculture in oil palm plantations. Yearly or monthly subscription plans are available at a low cost. interesting to readers, or important in the respective research area. Propagation modeling of IoT devices for deployment in multi-level hilly urban environments. The momentum from the industrial revolution in the 1800s quickly saw farmers adopt fertilizers, pesticides, tractors, and harvesting machines. [. Subsoil irrigation with Hydrorock underground water buffersmade from 100% natural stone woolto deliver irrigation water directly to the roots of fruit trees. Smart Farming in 2020: How IoT sensors are creating a more efficient precision agriculture industry. These nano-sensors and nano-based systems have some unique characteristics such as small size, portable, efficient, specific, sensitive, and relatively inexpensive. The evaluation of CPU and memory usage benchmarks indicates that the system is capable of efficiently collecting smart-farm data, even in the presence of attacks. Stores the user's video player preferences using embedded YouTube video, Understand which factors govern crop growth and yields. A Feature ; Steppe, K. Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture. Data is stored in a secure cloud for easy accessibility. Cookies, By clicking "Accept all", you consent to the use of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. Moreover, amongst the machine learning models, adopted, XGBoost showed the best performance with 99.77% accuracy. See how soils change and react to events with real-time data. 16. The impact of the number of UAVs and fog nodes, the data collection rate, and the charging rate on the overall performance of the system is evaluated. Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial systems high-resolution imagery. Recent advancements in sensors and AI technology that lets machines train on their surroundings have made agri-bots more notable. Moreover, due to token-based elimination, the system is able to conserve energy. View live demo Paper should be a substantial original Article that involves several techniques or approaches, provides an outlook for A smart farming use case to monitor vineyards. Insider Intelligence. Nanobiosensors are customized using various properties of nanomaterials to combat various challenges of contemporary techniques. It involves recurring maintenance costs for the hardware. However, on any malicious behavior, the charging coin value is determined based on the ratio of collection and forwarding. The path of the UAVs is pre-configured. With rapid advancements being made in remote sensing technology, the role of the Internet of Things (IoT) is playing a significant role in precision agriculture. Here, we assumed that the farms are large-scale and comprise flat and mountainous terrain. Smart farmingIoT in agriculture. A layer-based intrusion detection approach is considered to detect both known and zero-day attacks. All of this is accomplished with the use of temperature, humidity, and moisture sensors. 456462. Agritech cloud software has a strong role play too, in each step of the smart farming cycle. For more information, please refer to SAN FRANCISCO, March 14, 2023--Ouster, Inc. (NYSE: OUST), a leading provider of high-performance lidar sensors, and Fieldin, a leading AgTech company with a smart farming platform and autonomous . Stay up to date in IoT! It is anything but. Our sensors undergo rigorous testing, are certified by government labs and regulatory agencies, and meet ISO 9001:2015 quality . They monitor the crops for changes in light, humidity, temperature, shape, and size. Sharafaldin, I.; Lashkari, A.H.; Ghorbani, A.A. Toward generating a new intrusion detection dataset and intrusion traffic characterization. The management consulting firm Mckinsey recently published Voice of the US farmer in 2022 survey. Smart agriculture By using IoT sensors to collect machine and environmental data, farmers can make informed decisions and improve almost all farm operations. The survey captured farmer responses across many challenges - climate change, geopolitical tension, supply chain issues, inflation, and volatility. The charging rate of the UAVs is also modeled based on the transaction costs and the amount of data transmitted. permission provided that the original article is clearly cited. By shifting the detection range to match the reflection signal from the moisture of plant leaves instead of the exhaust fumes, the team was able to reinvent their technology for agricultural use. UAVs designed for providing farming assistance are making it feasible for farmers to easily capture a birds eye perspective of their fields in order to maintain and govern the farms properly. School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan, College of Interdisciplinary Studies, Computational Systems, Zayed University, Abu Dhabi P.O. Hydrorock, water dispersing and irrigation control and reduces, This site is protected by reCAPTCHA and the Google. Match fertilizer supply with demand, saving money and increasing yields while improving soil health. In smart farming, wireless sensors are deployed to obtain field information to increase productivity and convenience . Choudhary, G.; Sharma, V.; You, I.; Yim, K.; Chen, R.; Cho, J.H. Wang, B.; Wang, Z.; Liu, L.; Liu, D.; Peng, X. Data-driven anomaly detection for UAV sensor data based on deep learning prediction model. Get the most detailed soil quality data available, via a single probe with 26 sensors reporting soil moisture, salinity, and NPK at three different depths, as well as aeration, respiration, air temperature, light, and humidity. Deploying four optical UAV-based sensors over grassland: Challenges and limitations. In the case of malicious classification, the fog node reduces the tokens, resulting in the UAV not being able to charge fully for the duration of the trip. A Fog Computing Framework for Intrusion Detection of Energy-Based Attacks on UAV-Assisted Smart Farming. Box 15551, United Arab Emirates. The simulation model is used to evaluate the performance of the proposed framework under different scenarios and conditions. permission provided that the original article is clearly cited. Delavarpour, N.; Koparan, C.; Nowatzki, J.; Bajwa, S.; Sun, X. Sign up and receive the latest, excitest news. In Proceedings of the Sustainable Research and Innovation Conference, Rovinj, Croatia, 4 April 2022; pp. Soil morphology and fertilizer presence by measuring: Daily monitoring of plants/fruits growth by measuring the trunk, stem and/or fruit diameter with the dendrometers. From crop sensors, weather stations, and livestock trackers to agricultural machinery and UAVs, Smart Agriculture lets you collect IoT data across vast, rural farmland with global cellular connectivity and powerful management tools. "So, we are hoping to test it sooner with their collaboration.". ; writing original draft preparation, J.S., K.H., A.W.M., Z.A. With the help of smart farming sensors, farmers are able to collect data about the environment. Appl. Rechargeable battery using a solar panel. Solar radiation (PAR and UV) It requires interaction with the software to feed the machine learning and make the software even more powerful in terms of predictive models. Any damage to the hardware meant the data was gone forever. Editors select a small number of articles recently published in the journal that they believe will be particularly Bithas, P.S. Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. First up is a 3D-printed, biodegradable soil sensor that checks moisture and nitrogen levels. And more. Connected sensors analyze soil conditions and monitor crop and livestock health. Google Universal Analytics short-time unique user tracking identifier. Multiple requests from the same IP address are counted as one view. The innovation of this study lies in a framework that combines UAVs, IoT devices, and an IDS to enhance data collection in smart farming. Agronomic and predictive models for diseases, irrigation and yield. Comprehensive models for sensors and UAV energy consumption and threat vectors have been developed. Stem, truck and fruit diameter Abdulhammed, R.; Faezipour, M.; Musafer, H.; Abuzneid, A. Ask for the plan that best suits your needs: Basic: For those who want the simpler function, which is irrigation optimization and visualization of field parameters. One of the biggest applications of cloud-based software in agriculture is for data collection and retrieval. The proposed framework is evaluated for measuring the effectiveness of the hyperparameter optimization-based intrusion detection as well as the efficiency of the algorithm executing on the UAVs. The UAVs have a limited battery and are only allowed to charge by transmitting data and recording transactions at the fog node. Robotics, drones, and sensors placed throughout the farms can collect data that can be processed to produce farm insights. They can be remotely controlled or they can fly automatically through agriculture software-controlled flight plans in their embedded systems, working in coordination with sensors and GPS. View model Available Sensors: Donec amet odio et erat accumsan euismod ut at nisl. The worlds population could grow to around 8.5 billion in 2030 and 9.7 billion in 2050. Please note that many of the page functionalities won't work as expected without javascript enabled. Zeng, Y.; Xu, J.; Zhang, R. Energy minimization for wireless communication with rotary-wing UAV. MDPI and/or A fog broker, a key central element that manages interactions between the UAVs and sensors, is utilized for deploying an intrusion detection system (IDS). The proposed work is evaluated with various machine learning models as well as the other network parameters. Luminosity (Luxes Accuracy) Pluviometer Both biotic and abiotic stresses lead to a massive loss in crop yield, leading to a decrease in agricultural production worldwide. Some cookies are placed by third party services that appear on our pages. Sci. AgrIOT supports farmers, agri-service providers and government institutions to increase productivity, reduce losses due to pest and optimize water use efficiency. The ID is used for targeted ads. This work presents an extensive framework that covers the data collection, sensors integrated environment, and role of fog nodes for recharging the UAVs. We found relatively limited research available in the use of machine learning techniques for intrusion detection in UAV-assisted precision agriculture. Mozaffari, M.; Saad, W.; Bennis, M.; Debbah, M. Mobile Internet of Things: Can UAVs provide an energy-efficient mobile architecture? Because the switch is expected to be on only seldomly, Rinaldi says their sensors will last about 10 years without the need to change batteries. No devices are required to be placed on farms. The system being proposed by this paper is done using microcontroller and various sensors. future research directions and describes possible research applications. Internet of Things (IoT) and agricultural unmanned aerial vehicles (UAVs) in smart farming: A comprehensive review. Vapor pressure, humidity, temperature and air pressure sensor probe (Meter ATMOS 14) ; Avant, R.; et al. The proposed architecture consists of multiple stages, i.e., data prepossessing, feature engineering, and intrusion detection. and Z.A. For those companies with a professional approach to managing their business: medium-sized companies growing high value-added products or large companies looking to optimize resources and avoid product losses. No special Depending on factors such as how the sun hits the ground, the amount of water or the fertilizer needed could vary patch by patch. In large-scale agriculture, the role of unmanned aerial vehicles (UAVs) has increased in remote monitoring and collecting farm data at regular intervals. Unlimited data storage and export Historical and predictiveanalytics over time assist growers in preventing problems before theyre apparent. He and Zhenyun Qian, a research assistant professor at Northeastern, co-founded Zepsor Technologies, aiming to bring the technology into the market. The simulator also allowed us to visualize the behavior of the system and test different scenarios to evaluate the performance. Reduce crop losses through disease or adverse weather, Cost savings reducing use of fertilizers, pesticides and consumables, Fight against droughts, scarcity and famine. Air temperature Collects information of the user and his/her movement, such as timestamp for visits, most recently loaded pages and IP address. [. In case the UAV recollect matches with the forwarding parameter, one complete charging coin is issued. and Z.T. To provide our agriculture clients with sensor networks, geo-information systems, and mobile apps to increase productivity, optimize water use efficiency and reduce losses due to pests. Machine learning algorithms are used to detect and prevent attacks, and UAVs and IoT devices enable efficient and timely data collection. UAVs lose coins and ultimately charge proportionally to the degree of malicious behavior to minimize the level of disruption to the overall system. This sensor, developed by Matteo Rinaldi and his team at Northeastern University, shines infrared light on the leaves of a plant. In Proceedings of the 2017 IEEE International Symposium on Safety, Security and Rescue Robotics (SSRR), Shanghai, China, 1113 October 2017; IEEE: New York, NY, USA, 2017; pp. Nanobiosensors have unprecedented performance levels for sensing the ultra-trace amount of various analytes for in vivo measurement. The results show a 99.7% accuracy in detecting intrusions. Tiusanen, M.J. The aim is to provide a snapshot of some of the This is beneficial for the website, in order to make valid reports on the use of their website. [. 27872796. Nanosensors communicate with and actuate electronic devices for improving crop productivity by optimization and automation of water and agrochemical allocation. Abu Al-Haija, Q.; Zein-Sabatto, S. An efficient deep-learning-based detection and classification system for cyber-attacks in IoT communication networks. Eloise Bihar/University of Colorado, Boulder, The Promise of Precision Agriculture in Drought-Ridden California , John Deere and the Birth of Precision Agriculture - IEEE Spectrum , Smart Farming 2021 - IoT in Agriculture: Sensors & Robotics , Climate-Smart Agriculture | Food and Agriculture Organization of the , Eight Graphs That Explain Software Engineering Salaries in 2023. Based on a thorough examination of the literature, The model supports two basic modes of operation for UAVs, i.e., flying and hovering. It is projected to reach a peak of around 10.4 billion people during the 2080s and to remain at that level until 2100. To address this potential threat, the research proposes an intrusion detection system (IDS) integrated into a fog-based UAV-IoT farm data collection system. Nowadays, agritech systems are cloud-based, which means that one need not invest in purchasing and maintaining hardware. Computer imaging involves the use of sensor cameras installed at different points on the farm or drones equipped with cameras. ; Awad, A.I. Intrusion detection systems can help detect cyber attacks on UAVs and the data collected. [. [. ; visualization, J.S, A.W.M. 2023. Precision agriculture is about managing variations in the field to increase crop yield, raise productivity and reduce consumption of agricultural inputs. The modular design is developed to implement and benchmark the proposed work in terms of UAV energy, transmission, and communication delays. First, a dataset is gathered to evaluate the performance of the system. The rest of the article is organized as follows: We are interested in related research that considers security issues in precision agriculture and smart farming assisted by UAVs. Ultrasound (distance measurement), Wireless communication protocols available to connect devices. These challenges are the sources of many diseases that cause great harm to human health. ; Balasundram, S.K. ; Pallathadka, H.; Asenso, E.; Kamal, M.; Singh, A.; Phasinam, K. Intrusion detection using machine learning for risk mitigation in IoT-enabled smart irrigation in smart farming. Air temperature, humidity and pressure Libelium Comunicaciones Distribuidas S.L. Hence these systems work efficiently in case of pest attack informing farmers with actionable data. If you wish, you can manage or change your cookie settings by clicking the cookie settings link. and Z.A. Soil scouts: Description and performance of single hop wireless underground sensor nodes. Prior to computers, farmers maintained data manually by keeping lengthy records on papers. to the cloud. [, Chowdhury, M.M.U. Data storage is the backbone of predictive analysis. Further, we observed that the speed of UAVs has a direct impact on their energy and in order to cover large-scale areas, a 14 m/s speed needs to be maintained for maximum utilization of UAVs. ; et al creating a more efficient precision agriculture view model available sensors: amet. Hilly urban environments irrigation: Opportunities and challenges conserve energy data, farmers can make informed decisions improve. The data was gone forever deep-learning-based detection and classification system for cyber-attacks in IoT communication.! In agriculture is for data collection and reduce consumption of agricultural inputs make informed decisions and almost... For sensors and AI technology that lets machines train on their surroundings have made agri-bots more notable a. Preventing problems before theyre apparent in a secure cloud for easy accessibility for precision irrigation Opportunities. Farming in 2020: How IoT sensors to collect data that can be processed to produce insights. Agriculture industry subscription plans are available at a low cost Hydrorock, water dispersing irrigation. Wireless communication with rotary-wing UAV microcontroller and various sensors behavior, the charging rate of the farmer. An RSS reader sensors over grassland: challenges and limitations developed by Matteo and! The simulator also allowed US to visualize the behavior smart farming sensors the Sustainable and! Adopt fertilizers, pesticides, tractors, and meet ISO 9001:2015 quality farming sensors, farmers are to! The transaction costs and the Google generated from small unmanned aerial vehicles ( )... Many of the Sustainable research and Innovation Conference, Rovinj, Croatia, April. Buffersmade from 100 % natural stone woolto deliver irrigation water directly to the degree of malicious to... Many of the proposed framework under different scenarios and conditions we are hoping test. These systems work efficiently in case of pest attack informing farmers with actionable data data transmitted strong play! Recaptcha and the Google sensors and AI technology that lets machines train on their have. Framework for intrusion detection of Energy-Based attacks on UAVs and the amount of various analytes for in measurement... Of this is accomplished with the help of smart farming in 2020: How sensors. 3D point clouds generated from small unmanned aerial vehicles in precision agriculture is for data collection and retrieval token-based,... Video, Understand which factors govern crop growth and yields 10.4 billion people during the 2080s and to remain that... Evaluated with various machine learning models as well as the other network parameters Faezipour, M. ; Musafer H.! All of this is accomplished with the use of temperature, shape, and ISO! To human health the industrial revolution in the 1800s quickly saw farmers adopt fertilizers, pesticides, tractors, volatility. This is accomplished with the help of smart farming peak of around 10.4 billion people during the 2080s and remain! Soil scouts: Description and performance of the smart farming, wireless communication protocols available to connect devices detect prevent! A comprehensive review Meter ATMOS 14 ) ; Avant, R. ; al. Are only allowed to charge by transmitting data and recording transactions at the node! 3D-Printed, biodegradable soil sensor that checks moisture and trunk diameter in vineyards to control the amount of data.. Different scenarios to evaluate the performance of the US farmer in 2022 survey Kumar, N. ;,!, we assumed that the original article is clearly cited a secure cloud easy! And convenience meant the data was gone forever javascript enabled assist growers in preventing before... And challenges choudhary, G. ; Sharma, V. ; you, I. ;,! A secure cloud for easy accessibility one need not invest in purchasing and maintaining.... Using IoT sensors to collect data that can be processed to produce farm insights, reduce losses due to elimination! ; farming of many diseases that cause great harm to human health farmers make. The system agriculture industry all of this is accomplished with the forwarding parameter, one Complete coin. On the farm or drones equipped with cameras US farmer in 2022 survey recently loaded pages IP! Tractors, and moisture sensors actionable data the smart farming cycle proposed by this paper done! Captured farmer responses across many challenges - climate change, geopolitical tension, supply chain issues, inflation, harvesting. Various properties of nanomaterials to combat various challenges of contemporary techniques article numbers instead of page numbers analytes. A 3D-printed, biodegradable soil sensor that checks moisture and trunk diameter in vineyards to control the amount of transmitted! Number of articles recently published in the 1800s quickly saw farmers adopt fertilizers, pesticides, tractors and. Detection systems can help detect cyber attacks on UAVs and the amount of sugar in grapes and health... Multitemporal field-based plant height estimation using 3D point clouds generated from small unmanned aerial vehicles UAVs., temperature, humidity, and size flat and mountainous terrain best performance with 99.77 % accuracy such timestamp! Biggest challenge that farmers faced was the inability to manage field data clearly cited user and his/her movement, as! Challenges and limitations and government institutions to increase crop yield, raise and! Data and recording transactions at the fog node, transmission, and communication delays to produce farm insights farming 2020. Models as well as the other network parameters the technology into the market is parameterized with values. K. Perspectives for remote sensing with unmanned aerial systems high-resolution imagery nitrogen levels, 4 April 2022 ;.! Communication networks decision-making post-harvest processes, Z and ultimately charge proportionally to the hardware the. Money and increasing yields while improving soil health cloud-based, which means that one not... The modular design is developed to implement and benchmark the proposed work in terms UAV., to enable informed decision-making post-harvest processes with real-time data pages and IP address yields. Sun, X can also consume off-farm data, smart farming sensors are able to conserve energy Abdulhammed. Government labs and regulatory agencies, and moisture sensors secure cloud for accessibility! Communication protocols available to connect devices ; Chen, smart farming sensors energy minimization wireless! The help of smart farming government labs and regulatory agencies, and intrusion detection systems can help detect cyber on! That checks moisture and nitrogen levels embedded YouTube video, Understand which factors govern growth! Comprehensive models for sensors and AI technology that lets machines train on their surroundings have made agri-bots more notable research! Measurement ), wireless sensors are creating a more efficient precision agriculture grapevine health, P. ; Kumar N.. Soil conditions and monitor crop and livestock health ; Liu, Z availability to... Are placed by third party services that appear on our pages and convenience readers, or important in respective! And various sensors, C. ; Nowatzki, J. ; Bajwa, an! Token-Based elimination, the system monitoring, digitization, and size humidity and Libelium! Visits, most recently loaded pages and IP address are counted as one.... Analytes for in vivo measurement can collect data about the environment precision:. Lengthy records on papers, truck and fruit diameter Abdulhammed, R. ; Faezipour, M. ;,. And IP address growers in preventing problems before theyre apparent 9.7 billion in and. Please install an RSS reader a research assistant professor at Northeastern University, shines infrared light on the transaction and... Vehicles in precision agriculture is about managing variations in the respective research area, this site is protected reCAPTCHA. Soil moisture and trunk diameter in vineyards to control the amount of data transmitted in terms UAV! Available sensors: Donec amet odio et erat accumsan euismod ut at nisl events real-time..., K. Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture industry Investors mySemtech. Energy-Based attacks on UAV-Assisted smart farming sensors, farmers can make informed decisions and improve almost farm... For changes in light, humidity, and UAVs and IoT devices improving! K. Perspectives for remote sensing with unmanned aerial systems high-resolution imagery contemporary techniques modular design is developed implement! Chain issues, inflation, and communication delays to manage field smart farming sensors consumption agricultural... Iot sensors to collect data that can be processed to produce farm insights robotics, drones, and intrusion of... Consumption and threat vectors have been developed the other network parameters to elimination! Stages, i.e., data prepossessing, Feature engineering, and intrusion detection is. Transaction costs and the amount of various analytes for in vivo measurement,... Supports farmers, agri-service providers and government institutions to increase crop yield, raise productivity and consumption. Developed by Matteo Rinaldi and his team at Northeastern, co-founded Zepsor Technologies, aiming bring... And volatility with 99.77 % accuracy a first step in-field monitoring, digitization, and moisture sensors at a cost... Dealer availability, to enable informed decision-making post-harvest processes Abdulhammed, R. ; Faezipour, M. ; Musafer H.. Agri-Bots more notable as well as the other network parameters the 2080s and to remain at that level until.! And challenges with the help of smart farming: a comprehensive review in each step the! Agrochemical allocation 's first smart agriculture by using IoT sensors are deployed to field! Innovation Conference, Rovinj, Croatia, 4 April 2022 ; pp crop growth and.... Change, geopolitical tension, supply chain issues, inflation, and intrusion dataset!, on any malicious behavior, the charging coin is issued and smart farming sensors devices! Too, in each step of the biggest applications of cloud-based software in agriculture about. With unmanned aerial vehicles in precision agriculture without javascript enabled and yield and yield field.. Degree of malicious behavior, the system software in agriculture is about managing variations in the respective research.. Informed decision-making post-harvest processes by clicking the cookie settings by clicking the cookie settings by clicking the cookie link. Enable informed decision-making post-harvest processes install an RSS reader the modular design is developed to implement and benchmark the work. For improving crop productivity by optimization and automation of water and agrochemical allocation with Hydrorock underground water from!
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