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Smart Electronic Systems for Precision Agriculture
Full text linkL'abstract è presente nell'allegato / the abstract is in the attachmen
In-vivo proximal monitoring system for plant water stress and biological activity based on stem electrical impedance
Full text linkPopulation growth and global warming are the main threats to food production. Food security, producing enough food for the entire population, is becoming harder, and new strategies must be applied. Smart agriculture tackles this problem by integrating field sensors and data with the farmers’ knowledge to increase crop yield and reduce resource waste.This paper proposes a system to monitor the plant water stress status. This system monitors the plant directly and does not rely on environmental sensors. Acquired data are sent to a remote server thanks to LoRa communication. The designed system is low-power and relies on a single battery with more than five years of expected lifetime. The system monitors the trunk electrical impedance of plants thanks to a relaxation oscillator with a portion of the trunk in the feedback loop. This way, changes in the impedance are reflected in changes in the oscillator frequency.Two systems were installed directly in the fields and connected to apple trees. Statistical analyses were performed on the acquired data. The correlation between the trunk frequency values and the soil water potential is above 75% for both plants.The proposed system is low-power and low-cost and could be directly adopted in the fields. It can detect the water status of plants directly, avoiding environmental sensors
Preliminary Steps Towards a Low Power Integrated Circuit for AgriTech: a Relaxation Oscillator for Stem Impedance Monitoring
Full text linkThe main challenges in modern agriculture involve addressing the disruptive environmental effects caused by crop and livestock production, which are essential for human survival. Emerging trends point towards a world of pervasive IoT (Internet of Things) nodes, where low-cost, low-power, and in-vivo plant sensors can detect abiotic and biotic stresses at the earliest stages. This paper presents a preliminary study of an integrable, low-power relaxation oscillator, consisting of a Schmitt trigger in a feedback loop with the plant’s stem to evaluate its health status. Simulations have been conducted to compare the energy consumption of this circuit with state-of-the-art electronic sensors, focusing on energy usage per measurement. The results indicate that this new solution can sense the plant’s health status with an energy consumption below 10 μJ per measurement, which is at least an order of magnitude lower than existing electronic systems found in the literature
Sensor system for water stress detection using in-plant transmitted signal amplitude evaluation
Full text linkEnvironmental sustainability has become a significant topic, especially in recent years. Extreme natural phenomena and food insecurity related to the rising world population have highlighted the need for a new approach to agriculture. Smart Agriculture solutions may represent a viable answer to boost productivity, reduce emissions, and optimize human labor through the utilization of several new technologies and techniques in the climate-change scenario. From this perspective, the following paper proposes a sensor system capable of evaluating the plant’s health status based on stem electrical impedance from a local and global point of view. In particular, the receiving system is able to sense the global stem impedance, monitoring the amplitude of a signal transmitted inside the plant itself. The system injects a square wave into the plant, and thanks to the proposed sensor, it is possible to read a frequency proportional to the amplitude of this signal collected from another point of the stem. The developed system has been tested on a tobacco plant, showing correlations of 0.94 and -0.97, respectively, for the local sensor and global sensor with respect to the soil water potential
Recurrent Neural Networks for Soil Moisture Prediction Leveraging Soil Matric Potential Data
Full text linkSoil moisture is a parameter of paramount importance for a variety of applications, such as predicting floods and droughts, monitoring agricultural crop performance, and managing water supply. It can be measured in several ways, such as Volumetric Water Content (VWC) and soil matric potential. An experiment was carried out by placing soil matric potential sensors at depths of 20 centimeters and 40 centimeters within the root layer of an adult apple tree orchard to gather data every 10 minutes and to train some Recurrent Neural Network (RNN) models to predict future matric potential values at the depths of interest. Base RNN, Gated Recurrent Unit (GRU), and Long Short-Term Memory (LSTM) networks were employed to accomplish the aforementioned goal. Additionally, feature selection analysis was used to determine the best parameters to feed the models. The trained models give an accurate short-term prediction of 10 minutes, with an R2 of 0.9947, and a long-term prediction of 3 hours, with an R2 of 0.7922 at 20 centimeters
An Energy Autonomous and Battery-Free Plant’s Electrical Impedance Measurement System
Full text linkFood production is one of the main contributors to climate change and its impact is set to increase due to population growth. Smart agriculture aims at providing solutions to reduce food production and environmental impact while, at the same time, increasing crop production. This paper proposes a system based on STDES-BTAG01 by STMicroelectronics to monitor in-vivo stem electrical impedance, which is a parameter that has recently demonstrated its efficacy in assessing information about plants' water stress status. The developed system is completely battery-free and equipped with a wireless communication module to transmit the acquired data. It is powered by a small amorphous solar cell and transmits data to a base station exploiting the Bluetooth Low Energy (BLE) protocol. The system monitors the needed time to discharge a capacitor through the plant stem. After this, this span of time is used to compute the stem electrical impedance. Tests showed reading errors lower than 15% when dealing with impedance modules up to 180 k Omega. System characteristics (energy self-sufficiency, compactness, and low-power consumption) make the system implementable in the fields
Ask the plants directly: Understanding plant needs using electrical impedance measurements
Full text linkFood security is a major problem nowadays. Ensuring enough food for the entire human population is becoming
harder due to climate change and world population growth. Smart agriculture is a promising solution: integrating
sensors and data analysis in agriculture is leading to a reduction of food production waste and an increase in
production yield. However, currently environmental monitoring is not sufficient since different plants may have
disparate reactions even if their environmental conditions are similar. This paper shows a novel way of under-
standing plant status based on direct measurement of in vivo stem electrical impedance. This was achieved with a
system designed by the authors and validated by showing relations (correlation and Granger’s causality) between
stem electrical impedance and environment parameters. Validation was accomplished by monitoring and
analyzing multiple plants at the same time. Statistical analysis showed a correlation of up to 95% between
impedance and soil moisture, and that soil moisture variations caused variation in the impedance of the plants
Wappfruit - an automatic system for drip irrigation in orchards based on real-time soil matric potential data
Full text linkWater is a not-so-renewable resource. Agriculture is impacting for more than 70% of fresh water use worldwide. Considering the increase of population it is fundamental to act in order to reduce water usage. The WAPPFRUIT project aims to design an automatic irrigation system, based on data of water availability in the soil gathered directly in the orchards. Matric potential data are used to determine the exact water demand of the trees, thanks to specific thresholds adapted to the actual soil and crop type. Furthermore, an electronic system based on simple, small, and ultra-low-power devices works together an automatic algorithm to manage the watering events. We tested this approach in three orchards in north-west Italy, comparing our approach to the one used by the farmers. The results show an average water saving of nearly 50% keeping the fruit production comparable to the reference solution. This approach is a clear example of how electronics and technology can really impact agriculture and food production
FruitGuard - System for the Management, Protection, and Enhancement of the Fruit Supply Chain
Full text linkFruit harvesting and traceability are vital in fruit crop production for maintaining quality and minimizing waste. The proposed system integrates wearable smart devices, electronic labels, QR codes, and cloud-based software to track the entire production process, from harvesting to distribution. Smart devices provide relevant information to harvesters, while electronic labels identify location and fruit type. Reading/writing modules record data like container weights, and RFID tags monitor crate locations. An additional study optimized RFID tag orientation in cold storage. QR codes offer detailed product information to consumers, and the management software ensures data collection, storage, and analysis while prioritizing privacy and security. In summary, the system aims to optimize fruit production management and enhance traceability across the supply chain
Long-Range Low-Power Electronic System for Drip Irrigation in Precision Agriculture
Full text linkNowadays, food security is threatened by population growth, wars, climate change, and desertification due to human activities. Precision agriculture is a novel concept to minimize the usage of natural resources in the agriculture field, mitigating the anthropological effects. This is possible by adopting electronic systems to measure plants' requirements and to make optimal decisions on the crop, avoiding wastefulness. One critical aspect of agriculture is the handling of potable water: an essential resource for all living entities. This paper proposes a long-range, low-power electronic system for drip irrigation in orchards, especially Actinidia and apple trees, to control the distributed water to the cultivars. In this way, the irrigation cycle depends on the plants' needs, saving water and energy resources. The node communicates using LoRa radiofrequency protocol, and it can be used in rural areas where no internet connection is present
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