{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T03:53:04Z","timestamp":1768881184412,"version":"3.49.0"},"reference-count":72,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T00:00:00Z","timestamp":1768780800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62402003"],"award-info":[{"award-number":["62402003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Anhui Science and Technology University Talent Introduction Project","award":["RCYJ202402"],"award-info":[{"award-number":["RCYJ202402"]}]},{"name":"Research and development of intelligent fault diagnosis method for solar insecticidal lamp","award":["20250009"],"award-info":[{"award-number":["20250009"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JSAN"],"abstract":"<jats:p>Ensuring food security requires innovative, sustainable pest management solutions. The Solar Insecticidal Lamp Internet of Things (SIL-IoT) represents such an advancement, yet its reliability in harsh, variable outdoor environments is compromised by frequent component and sensor faults, threatening effective pest control and data integrity. This paper presents a comprehensive survey on fault detection (FD) for SIL-IoT systems, systematically analyzing their unique challenges, including electromagnetic interference, resource constraints, data scarcity, and network instability. To address these challenges, we investigate countermeasures, including blind source separation for signal decomposition under interference, lightweight model techniques for edge deployment, and transfer\/self-supervised learning for low-cost fault modeling across diverse agricultural scenarios. A dedicated case study, utilizing sensor fault data of SIL-IoT, demonstrates the efficacy of these approaches: an empirical mode decomposition-enhanced model achieved 97.89% accuracy, while a depthwise separable-based convolutional neural network variant reduced computational cost by 88.7% with comparable performance. This survey not only synthesizes the state of the art but also provides a structured framework and actionable insights for developing robust, efficient, and scalable FD solutions, thereby enhancing the operational reliability and sustainability of SIL-IoT systems.<\/jats:p>","DOI":"10.3390\/jsan15010011","type":"journal-article","created":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T14:58:54Z","timestamp":1768834734000},"page":"11","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Survey on Fault Detection of Solar Insecticidal Lamp Internet of Things: Recent Advance, Challenge, and Countermeasure"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7818-1030","authenticated-orcid":false,"given":"Xing","family":"Yang","sequence":"first","affiliation":[{"name":"College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-8070-6561","authenticated-orcid":false,"given":"Zhengjie","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6700-9347","authenticated-orcid":false,"given":"Lei","family":"Shu","sequence":"additional","affiliation":[{"name":"NAU-Lincoln Joint Research Center of Intelligent Engineering, Nanjing Agricultural University, Nanjing 210031, China"},{"name":"Guangdong Provincial Key Laboratory for Green Agricultural Production and Intelligent Equipment, School of Environmental Science and Engineering, Guangdong University of Petrochemical Technology, Maoming 525000, China"},{"name":"School of Engineering, University of Lincoln, Lincoln LN6 7TS, UK"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0365-710X","authenticated-orcid":false,"given":"Fan","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Automation, Jiangsu Normal University, Xuzhou 221116, China"}]},{"given":"Xuanchen","family":"Guo","sequence":"additional","affiliation":[{"name":"College of Intelligent Manufacturing, Anhui Science and Technology University, Chuzhou 233100, China"}]},{"given":"Xiaoyuan","family":"Jing","sequence":"additional","affiliation":[{"name":"School of Computer, Guangdong University of Petrochemical Technology, Maoming 525000, China"},{"name":"School of Computer Science, Wuhan University, Wuhan 430072, China"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"36","DOI":"10.1186\/s40066-021-00318-5","article-title":"Impact of climate change on biodiversity and food security: A global perspective\u2014A review article","volume":"10","author":"Muluneh","year":"2021","journal-title":"Agric. 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