Embedded intelligent micro / nano sensor system for precision agriculture and plant health management

Abstract

An embedded plant health monitoring system comprising a MEMS or NEMS sensor chip for measuring at least sap flow rate, chlorophyll fluorescence, electrical conductivity or pH value and gas exchange in a plant; interface electronics and a controller for acquiring and preprocessing the measured values; a wireless transceiver for at least one of the standards BLE, LoRa, Wi-Fi, 5G or NFC; and a renewable energy utilization subsystem comprising at least one plant biofuel cell, a piezoelectric nanogenerator, a miniature solar cell or a biodegradable battery, wherein the system transmits data in real time for precision agriculture.

Description

Application area of ​​the invention

[0001] The invention relates to bioelectronic sensor systems for plants that combine MEMS / NEMS sensor chips, energy harvesting and IoT communication to monitor physiological and environmental parameters for precision agriculture. Background of the invention

[0002] Plant bioelectronics and flexible, plant-worn sensors enable real-time monitoring of hydration, stomatal behavior, microclimate, and related parameters using nanomaterials and energy-efficient electronics attached to leaves or stems. Review articles describe plant-integrated sensors that measure humidity, temperature, light, and gases, and whose data can be remotely accessed via Bluetooth. They highlight the potential of biohybrid devices for agronomy. Energy harvesting using piezoelectric, triboelectric, and thermoelectric nanogenerators, as well as plant / microbial biofuel cells, has been proposed to power distributed sensors autonomously, thus supporting the long-term use of IoT devices in agriculture.These advances open the possibility for a unified embedded system that captures sap flow, chlorophyll fluorescence, ion conductivity, pH and gas exchange, and features sustainable power supply and long-range telemetry for farm analysis. Summary of the invention

[0003] The invention relates to an embedded plant health system comprising a MEMS / NEMS chip with miniature sensors for sap flow rate, chlorophyll fluorescence, electrical conductivity, pH value, and gas exchange; interface electronics for signal processing; a wireless module supporting BLE, LoRa, Wi-Fi, 5G, or NFC; and a renewable energy subsystem utilizing one or more plant-powered biofuel cells, piezoelectric nanogenerators, miniature solar cells, or biodegradable batteries. The sensor data are transmitted in real time to a gateway or mobile device and processed by AI models that derive plant stress, disease onset, and resource requirements, and from this derive recommendations for irrigation, fertilization, and plant protection.

[0004] In embodiments, the device is configured as a minimally invasive probe or as a pluggable leaf / stem module with biocompatible adhesives and encapsulation, and uses low-noise amplifiers, optical excitation / detection for chlorophyll fluorescence, microfluidic channels for sap measurement, and gas sensors for CO2 / O2 exchange, all controlled by an extremely energy-efficient duty-ratio control logic. Detailed description

[0005] An integrated MEMS / NEMS sensor chip: a thermal or microfluidic sap flow microsensor that comes into contact with xylem / phloem conducting pathways and is provided with protective coatings to minimize tissue damage; an optical unit with excitation LEDs and photodiodes for measuring chlorophyll fluorescence indices, which provide information about the efficiency of photosystem II; Ion-selective electrodes or conductivity microelectrodes for pH and nutrient ion proxies, with reference electrodes and on-chip temperature compensation. Miniaturized gas sensors for measuring CO2 and O2 exchange at leaf level, supported by a micro-spacer to maintain a stable boundary layer.

[0006] Signal processing ASICs amplify, filter, and multiplex weak biosignals. A microcontroller coordinates sampling schedules, calibrations, and in-device preprocessing. Wireless telemetry supports various connections: BLE for proximity detection, LoRa for energy-efficient long-range networking of farms, Wi-Fi / 5G (where infrastructure is available), and NFC for maintenance and rapid diagnostics without powering the radios. Antenna design and optimized operating time extend the device's lifespan.

[0007] The energy system combines renewable energy sources: a microbial plant / biofuel cell that utilizes electrochemical gradients in the rhizosphere or plant tissue; a piezoelectric or triboelectric nanogenerator that harvests vibrational energy from wind-induced leaf movements; and a miniature solar cell for daily charging. A biodegradable or thin-film battery serves as energy storage, and an energy manager ensures maximum power point tracking and extremely low leakage currents. According to the literature, such nanogenerators can sustainably power low-power IoT sensors.

[0008] The packaging uses biocompatible, breathable encapsulation materials and flexible substrates that conform to the plant surface without hindering growth. Attachment options include snap-on leaf patches with an air gap to prevent condensation and stem sleeves with gentle strain relief. These approaches mirror the methods used in portable plant sensors for measuring transpiration and hydration.

[0009] Edge AI calculates features such as diurnal sap flow profiles, chlorophyll fluorescence values, gas exchange anomalies, and pH / EC trends, generating stress indices and disease risk assessments. Where possible, the models run directly on the device, with summaries uploaded regularly to conserve bandwidth. Gateways aggregate the data, perform fleet analyses, and recommend precise water and nutrient dosing.

[0010] Data management includes encryption, authenticated LoRa connections, secure key storage, and consent-based data sharing with farm management systems. Firmware updates are signed; in case of emergency, power-saving mode is activated by default.

[0011] In such a deployment, multiple sensors can be distributed across representative plants per plot; AI models interpolate the conditions at the stand level and detect emerging stress, enabling proactive interventions that improve yield and resource efficiency.

Claims

[1] An embedded plant health monitoring system comprising a MEMS or NEMS sensor chip for measuring at least sap flow rate, chlorophyll fluorescence, electrical conductivity or pH and gas exchange in a plant; interface electronics and a controller for acquiring and preprocessing the measured values; a wireless transceiver for at least one of the standards BLE, LoRa, Wi-Fi, 5G or NFC; and a renewable energy utilization subsystem comprising at least one plant biofuel cell, a piezoelectric nanogenerator, a miniature solar cell or a biodegradable battery, wherein the system transmits data in real time for precision agriculture. [2] System according to claim 1, wherein the controller executes AI models configured to derive indicators of plant stress and disease outbreak from daily profiles of sap flow, chlorophyll fluorescence, gas exchange and ion metrics, and to generate recommendations for irrigation, nutrient dosing or protection. [3] System according to claim 1, wherein the sensor chip is configured as a minimally invasive probe or as a flexible module mounted on leaves or stems with biocompatible encapsulation and cyclic operation to reduce energy consumption and tissue stress. [4] System according to claim 1, wherein the renewable energy subsystem comprises an energy manager configured to detect and control the input powers of the biofuel cell and the nanogenerator in order to maintain low-power telemetry over long distances.