Ag-IoT for crop and environment monitoring: Past, present, and future

CONTEXT: Automated monitoring of the soil-plant-atmospheric continuum at a high spatiotemporal resolution is a key to transform the labor-intensive, experience-based decision making to an automatic, data-driven approach in agricultural production. Growers could make better management decisions by leveraging the real-time field data while researchers could utilize these data to answer key scientific questions. Traditionally, data collection in agricultural fields, which largely relies on human labor, can only generate limited numbers of data points with low resolution and accuracy. During the last two decades, crop monitoring has drastically evolved with the advancement of modern sensing technologies. Most importantly, the introduction of IoT (Internet of Things) into crop, soil, and microclimate sensing has transformed crop monitoring into a quantitative and data-driven work from a qualitative and experience-based task. OBJECTIVE: Ag-IoT systems enable a data pipeline for modern agriculture that includes data collection, transmission, storage, visualization, analysis, and decision-making. This review serves as a technical guide for Ag-IoT system design and development for crop, soil, and microclimate monitoring. METHODS: It highlighted Ag-IoT platforms presented in 115 academic publications between 2011 and 2021 worldwide. These publications were analyzed based on the types of sensors and actuators used, main control boards, types of farming, crops observed, communication technologies and protocols, power supplies, and energy storage used in Ag-IoT platforms

Internet of Things Applications in Precision Agriculture: A Review

The goal of this paper is to review the implementation of an Internet of Things (IoT)-based system in the precision agriculture sector. Each year, farmers suffer enormous losses as a result of insect infestations and a lack of equipment to manage the farm effectively. The selected article summarises the recommended systematic equipment and approach for implementing an IoT in smart farming. This review's purpose is to identify and discuss the significant devices, cloud platforms, communication protocols, and data processing methodologies. This review highlights an updated technology for agricultural smart management by revising every area, such as crop field data and application utilization. By customizing their technology spending decisions, agriculture stakeholders can better protect the environment and increase food production in a way that meets future global demand. Last but not least, the contribution of this research is that the use of IoT in the agricultural sector helps to improve sensing and monitoring of production, including farm resource usage, animal behavior, crop growth, and food processing. Also, it provides a better understanding of the individual agricultural circumstances, such as environmental and weather conditions, the growth of weeds, pests, and diseases

Une plate-forme sans fil pour electrochimique spectroscopie d'impédance

Avec l’émergence soutenue de capteurs et de dispositifs électrochimiques innovants, la spectroscopie d'impédance électrochimique est devenue l'un des outils les plus importants pour la caractérisation et la modélisation de la matière ionique et de l'interfaçage des capteurs. La capacité de détecter automatiquement, à l’aide de dispositifs électrochimiques peu couteux, les caractéristiques physiques et chimiques de la matière ionique ouvre une gamme d’application très variée pour la compréhension et l’optimisation des procédés ou interviennent les processus électrochimiques. Cette thèse décrit le développement d’une plate-forme microélectronique miniaturisée, connectée, multiplexée, et à faible coût pour la spectroscopie d'impédance diélectrique (SID) conçue pour les mesures électrochimiques in-situ et adaptée aux architectures de réseau sans fil. La plate-forme développée durant ce travail de maitrise a été testée et validée au sein d’une maille ZigBee et a été en mesure d'interfacer jusqu'à trois capteurs SID en même temps et de relayer l'information à travers le net Zigbee pour l'analyse de données et le stockage. Le système a été construit à partir de composants microélectroniques disponibles commercialement et bénéficie des avantages d'une calibration système on-the-fly qui effectue la calibration du capteur de manière aisée. Dans ce mémoire de maitrise, nous rapportons la modélisation et la caractérisation de senseurs électrochimiques de nitrate; notamment nous décrivons la conception microélectronique, la réponse d'impédance de Nyquist, la sensibilité et la précision de la mesure électrochimique, et les résultats de tests de la plate-forme pour les applications de spectroscopie d'impédance relatives à la détection du nitrate, de la détection de la qualité de l'eau, et des senseurs tactiles.The emergence of the various applications of electrochemical sensors and devices, electrochemical impedance spectroscopy became one of the most important tools for characterizing and modeling of the material and interfacing the sensors. The ability to sense in an automatic manner enables a wide variety of processes to be better understood and optimized cost-effectively. This thesis describes the development of a low-cost, miniaturized, multiplexed, and connected platform for dielectric impedance spectroscopy (DIS) designed for in-situ measurements and adapted to wireless network architectures. The platform has been tested and used as a DIS sensor node on a ZigBee mesh and was able to interface up to three DIS sensors at the same time and relay the information through the Zigbee net for data analysis and storage. The system was built from commercial microelectronics components and benefits from an on-the-fly calibration system that makes sensor calibration easy. The thesis reports characterizing and modeling of two electro-chemical devices (i.e. nitrate sensor and optically-transparent electrically-conductive glasses) and also describes the microelectronics design, the Nyquist impedance response, the measurement sensitivity and accuracy, and the testing of the platform for in-situ dielectric impedance spectroscopy applications pertaining to fertilizer sensing, water quality sensing, and touch sensing

FogGIS: Fog Computing for Geospatial Big Data Analytics

Cloud Geographic Information Systems (GIS) has emerged as a tool for analysis, processing and transmission of geospatial data. The Fog computing is a paradigm where Fog devices help to increase throughput and reduce latency at the edge of the client. This paper developed a Fog-based framework named Fog GIS for mining analytics from geospatial data. We built a prototype using Intel Edison, an embedded microprocessor. We validated the FogGIS by doing preliminary analysis. including compression, and overlay analysis. Results showed that Fog computing hold a great promise for analysis of geospatial data. We used several open source compression techniques for reducing the transmission to the cloud.Comment: 6 pages, 4 figures, 1 table, 3rd IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics (09-11 December, 2016) Indian Institute of Technology (Banaras Hindu University) Varanasi, Indi

Towards In-situ Based Printed Sensor Systems for Real-Time Soil-Root Nutrient Monitoring and Prediction with Polynomial Regression

This dissertation explores how to increase sensor density in the agricultural framework using low-cost sensors, while also managing major bottlenecks preventing their full commercial adoption for agriculture, accuracy and drift. It also investigated whether low-cost biodegradable printed sensor sheets can result in improved stability, accuracy or drift for use in precision agriculture. In this dissertation, multiple electrode systems were investigated with much of the work focused on printed carbon graphene electrodes (with and without nanoparticles). The sensors were used in two configurations: 1) in varying soil to understand sensor degradation and the effect of environment on sensors, and 2) in plant pod systems to understand growth. It was established that 3) the sensor drift can be controlled and predicted 2) the fabricated low-cost sensors work as well as commercial sensors, and 3) these sensors were then successfully validated in the pod platform. A standardized testing system was developed to investigate soil physicochemical effects on the modified nutrient sensors through a series of controlled experiments. The construct was theoretically modeled and the sensor data was matched to the models. Supervised machine learning algorithms were used to predict sensor responses. Further models produced actionable insight which allowed us to identify a) the minimal amounts of irrigation required and b) optimal time after applying irrigation or rainfall event before achieving accurate sensor readings, both with respect to sensor depth placement within the soil matrix. The pore-scale behavior of solute transport through different depths within the sandy soil matrix was further simulated using COMSOL Multi-physics. This work leads to promising disposable printed systems for precision agriculture

Internet of Things for Water Sustainability

The water is a finite resource. The issue of sustainable withdrawal of freshwater is a vital concern being faced by the community. There is a strong connection between the energy, food, and water which is referred to as water-food-energy nexus. The agriculture industry and municipalities are struggling to meet the demand of water supply. This situation is particularly exacerbated in the developing countries. The projected increase in world population requires more fresh water resources. New technologies are being developed to reduce water usage in the field of agriculture (e.g., sensor guided autonomous irrigation management systems). Agricultural water withdrawal is also impacting ground and surface water resources. Although the importance of reduction in water usage cannot be overemphasized, major efforts for sustainable water are directed towards the novel technology development for cleaning and recycling. Moreover, currently, energy technologies require abundant water for energy production. Therefore, energy sustainability is inextricably linked to water sustainability. The water sustainability IoT has a strong potential to solve many challenges in water-food-energy nexus. In this chapter, the architecture of IoT for water sustainability is presented. An in-depth coverage of sensing and communication technologies and water systems is also provided

IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water.

[EN] The in-line determination of chemical parameters in water is of capital importance for environmental reasons. It must be carried out frequently and at a multitude of points; thus, the ideal method is to utilize automated monitoring systems, which use sensors based on many transducers, such as Ion Selective Electrodes (ISE). These devices have multiple advantages, but their management via traditional methods (i.e., manual sampling and measurements) is rather complex. Wireless Sensor Networks have been used in these environments, but there is no standard way to take advantage of the benefits of new Internet of Things (IoT) environments. To deal with this, an IoT-based generic architecture for chemical parameter monitoring systems is proposed and applied to the development of an intelligent potassium sensing system, and this is described in detail in this paper. This sensing system provides fast and simple deployment, interference rejection, increased reliability, and easy application development. Therefore, in this paper, we propose a method that takes advantage of Cloud services by applying them to the development of a potassium smart sensing system, which is integrated into an IoT environment for use in water monitoring applications. The results obtained are in good agreement (correlation coefficient = 0.9942) with those of reference methods.FundingThis research was funded by Spanish Ministerio de Economia y Competitividad, Gobierno de Espana, grant number DPI2016-80303-C2-1-P.Campelo Rivadulla, JC.; Capella Hernández, JV.; Ors Carot, R.; Peris Tortajada, M.; Bonastre Pina, AM. (2022). IoT Technologies in Chemical Analysis Systems: Application to Potassium Monitoring in Water. Sensors. 22(3):1-16. https://doi.org/10.3390/s2203084211622