Next-Generation Intelligent Sensing for Green and Smart Agriculture

A Special Issue of Technologies (ISSN 2227-7080) belonging to the section "Information and Communication Technologies".

Deadline for manuscript submissions: 30 November 2026 | Viewed by 2154

Editor


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Guest Editor
College of Engineering, China Agricultural University, Beijing 100083, China
Interests: smart sensing; smart agriculture; internet of things; energy harvesting sensing; self-powered sensing; battery-free sensing; food monitoring
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Special Issue Information

Dear Colleagues,

The rapid advancement of intelligent sensing technologies is revolutionizing agriculture, enabling precise environmental monitoring, resource optimization, and sustainable practices. This Special Issue focuses on cutting-edge innovations in next-generation sensors, including nanobiosensors, self-powered sensing, and AI-driven IoT systems, tailored for green and smart farming. We invite contributions on topics such as the following:

  1. Real-time crop health monitoring;
  2. Automated irrigation;
  3. Pest detection;
  4. Energy-efficient data transmission;
  5. Energy harvesting and self-powered wireless sensing.

Emphasis is placed on applications that enhance yield, reduce waste, and minimize environmental impact. Original research, reviews, and case studies addressing challenges such as sensor deployment in diverse terrains and integration with smart farming platforms are welcome. Join us in exploring transformative solutions for a sustainable agricultural future.

Dr. Xinqing Xiao
Guest Editor

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Keywords

  • artificial intelligence
  • smart agriculture
  • green agriculture
  • intelligent sensing

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Published Papers (1 paper)

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Review

40 pages, 3102 KB  
Review
Plant Microbial Fuel Cell-Based Sensing for Smart Rice
by Ziyang Chen, Jianyu Wei, Hang Su, Qiyong Liang, Wei Yang, Chaohua Mo, Lingling Chen, Feng Liu, Jian Wang, Xinghan Chen and Xinqing Xiao
Technologies 2026, 14(6), 347; https://doi.org/10.3390/technologies14060347 - 10 Jun 2026
Viewed by 1301
Abstract
Facing global problems such as the energy crisis and climate change, in recent years, the bioelectrochemical system represented by plant microbial fuel cell (PMFC) has been widely studied. It is a frontier bioelectrochemical technology that combines plant photosynthesis, rhizosphere microbial metabolism, and electrochemical [...] Read more.
Facing global problems such as the energy crisis and climate change, in recent years, the bioelectrochemical system represented by plant microbial fuel cell (PMFC) has been widely studied. It is a frontier bioelectrochemical technology that combines plant photosynthesis, rhizosphere microbial metabolism, and electrochemical energy conversion. This paper focuses on the linkage application of PMFC and intelligent sensing technology in the paddy-field environment, systematically expounds the basic composition, working principle, and integration mode of this technology with paddy field ecology, and emphatically analyzes its realization path and application potential in self-powered external sensor deployment, rhizosphere biosensor, and multi-node sensor network integration. The analysis shows that PMFC has the unique advantage of in situ and continuous micro-power generation in flooded rice fields. Its output not only supports the intermittent operation of low-power sensors, but the output electrical signals can also reflect plant stress and environmental conditions, thereby possessing biosensing potential. However, the current system still faces key bottlenecks, such as low power density, easily disturbed electrical signals, and high cost of high-performance electrode materials, which restrict the actual deployment of rice fields. Through the collaborative optimization of electrode interface engineering, microbial community directional control, and low-power sensing fusion strategy, it is expected to promote the transformation of PMFC from principle verification to field intelligent monitoring application. Full article
(This article belongs to the Special Issue Next-Generation Intelligent Sensing for Green and Smart Agriculture)
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