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About

Jenq-Shiou Leu is a researcher whose work bridges the gap between advanced surveillance systems and the Internet of Things (IoT) for real-world applications. His key research areas include IoT system design, mobile surveillance, and embedded computing. Leu’s most impactful contribution is the design and implementation of a LoRa-based IoT scheme tailored for Indonesian rural areas, which has garnered 41 citations. This work addresses critical challenges in digitizing and monitoring remote regions, demonstrating how low-power wide-area networks can enable practical IoT solutions where traditional connectivity is limited. Earlier in his career, Leu focused on dynamic surveillance systems, notably developing a recognition-assisted surveillance system that integrates OSGi and OpenCV platforms. His series of papers on mobile home surveillance and remote mobile surveillance systems (2009–2011) advanced the mobility of both camera and viewer ends, allowing real-time event monitoring from mobile devices. These contributions, though with fewer citations, laid foundational work for flexible, real-time monitoring. Leu’s research is characterized by practical implementation and system integration, making his work valuable for engineers and researchers developing accessible, scalable IoT and surveillance technologies.