A Four-Port Reconfigurable Antenna Sensor of Sensing Multiple Parameters for Smart Agricultural Monitoring
In the transformation of future smart agriculture paradigms, Internet of Things (IoT) technology is regarded as a pivotal factor driving environmental perception in farming. Chipless radio frequency identification (CRFID) technology is a potential technology that will bring huge added value to advanced passive IoT-based sensing systems. However, developing CRFID sensors with controllable modes and integrated multiparameter integration remains a major challenge. In this article, we propose a novel reconfigurable four-port antenna-based sensor with multiparameter characteristics. By integrating multiple sensor arrays designed with special sensitive materials on the same plane, we achieve flexible channel reuse and sensing mode reconstruction. The sensor is completely passive and reusable, enabling long-term synchronous sensing and information transmission in critical areas where power supply is difficult to obtain. The small dimensions of the sensor increase susceptibility to coupling interference in multichannel and multiple sensing unit array designs. Therefore, we jointly optimize the sensor’s structure and layout to enhance isolation between sensor elements. Finally, we design and demonstrate a passive sensing system for monitoring relative humidity (hereafter called humidity) and pH levels, and verify the potential value of the passive multiparameter sensing system in future precision agriculture (PA) applications through experiments.
Authors
- Ajay K. Poddar (ORCID: https://orcid.org/0000-0002-2733-8517)
- Luyi Liu (ORCID: https://orcid.org/0000-0003-0774-1154)
- Mei Song Tong (ORCID: https://orcid.org/0000-0001-6317-1008)
- Dan Ni Lin
- Ulrich L. Rohde
Institutions
- Tongji University (CN)
- Synergy Microwave (United States) (US)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1109/jsen.2024.3520808
- Citations
- 5
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 3.00
Funders
- National Natural Science Foundation of China