Agniswar Paul

Papers

Total Citations

H-Index

About

Agniswar Paul is a researcher at the forefront of embedded systems and intelligent surveillance, with a focus on accessible, low-cost automation solutions. His most-cited work, "Implementation of Human Detection on Raspberry Pi for Smart Surveillance" (2020, 6 citations), addresses the growing demand for proactive security by integrating computer vision with compact, affordable hardware. Paul’s contribution lies in demonstrating that sophisticated human detection algorithms can be deployed on a Raspberry Pi, transforming a passive recording device into an active, real-time alert system. This approach not only enhances home and small-business security but also democratizes smart surveillance, making it feasible for widespread adoption. His research bridges the gap between high-end AI models and practical, resource-constrained environments, offering a blueprint for efficient edge computing. Paul’s work is particularly notable for its emphasis on scalability and real-world applicability, inspiring further exploration into embedded vision systems. By tackling the challenge of theft and insecurity through innovative hardware-software integration, he has laid a foundation for smarter, more responsive security infrastructure that is both cost-effective and accessible.