Precision Agriculture: Ultra-Compact Sensor and Reconfigurable Antenna for Joint Sensing and Communication
In this paper, a joint sensing and communication system is presented for smart agriculture. The system integrates an Ultra-compact Soil Moisture Sensor (UCSMS) for precise sensing, along with a Pattern Reconfigurable Antenna (PRA) for efficient transmission of information to the base station. A multiturn complementary spiral resonator (MCSR) is etched onto the ground plane of a microstrip transmission line to achieve miniaturization. The UCSMS operates at 180 MHz with a 3-turn complementary spiral resonator (3-CSR), at 102 MHz with a 4- turn complementary spiral resonator (4-CSR), and at 86 MHz with a 5-turn complementary spiral resonator (5-CSR). Due to its low resonance frequency, the proposed UCSMS is insensitive to variations in the Volume Under Test (VUT) of soil. A probe-fed circular patch antenna is designed in the Wireless Local Area Network (WLAN) band (2.45 GHz) with a maximum measured gain of 5.63 dBi. Additionally, four varactor diodes are integrated across the slots on the bottom side of the substrate to achieve pattern reconfiguration. Six different radiation patterns have been achieved by using different bias conditions of the diodes. In standby mode, PRA can serve as a means for Wireless Power Transfer (WPT) or Energy Harvesting (EH) to store power in a battery. This stored power can then be utilized to bias the varactor diodes. The combination of UCSMS and PRA enables the realization of a joint sensing and communication system. The proposed system's planar and simple geometry, along with its high sensitivity of 2.05 %, makes it suitable for smart agriculture applications. Moreover, the sensor is adaptive and capable of measuring the permittivity of various Material Under Test (MUT) within the range of 1 to 23.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
High precision control and deep learning-based corn stand counting algorithms for agricultural robot
This paper presents high precision control and deep learning-based corn stand counting algorithms for a low-cost, ultra-compact 3D printed and autonomous field robot for agricultural operations. Currently, plant traits, …
Model Predictive ControlVisual TrackingImage-based ground distance detection for crop-residue-covered soil
Conservation agriculture features a soil surface covered with crop residues, which brings benefits of improving soil health and saving water. However, one significant challenge in conservation agriculture lies in precise…
On-Air Deep Learning Integrated Semantic Inference Models for Enhanced Earth Observation Satellite Networks
Earth Observation (EO) systems are crucial for cartography, disaster surveillance, and resource administration. Nonetheless, they encounter considerable obstacles in the processing and transmission of extensive data, esp…
Data AugmentationDisaster ResponseDomain AdaptationEarth Observation+3AgriCruiser: An Open Source Agriculture Robot for Over-the-row Navigation
We present the AgriCruiser, an open-source over-the-row agricultural robot developed for low-cost deployment and rapid adaptation across diverse crops and row layouts. The chassis provides an adjustable track width of 1.…
Bitwise Systolic Array Architecture for Runtime-Reconfigurable Multi-precision Quantized Multiplication on Hardware Accelerators
Neural network accelerators have been widely applied to edge devices for complex tasks like object tracking, image recognition, etc. Previous works have explored the quantization technologies in related lightweight accel…
Object Tracking