IoT and Computer Vision for Enhanced Public Safety

The integration of Internet of Things (IoT) and Computer Vision has significantly revolutionized various industries, including smart cities, healthcare, transportation, and security. One of the most critical applications of this technological convergence is in street lighting systems. Traditional street lighting systems operate on fixed schedules or manual control, which often leads to inefficiencies in energy consumption and public safety. These systems frequently illuminate areas even when there is no pedestrian or vehicular movement, leading to excessive energy consumption and increased operational costs. Conversely, poorly lit or non-functional streetlights contribute to security risks, accidents, and increased crime rates in urban and rural areas.With the advent of smart lighting systems, powered by IoT and Computer Vision, the potential for optimizing energy usage and enhancing public safety has expanded tremendously. Object detection, a crucial aspect of computer vision, enables real-time identification and analysis of pedestrians, vehicles, and other objects in a given area.

Autorentext
Shiplu Das was born in India. He is currently associated with Department of Computer Science and Engineering, Adamas University, Kolkata, India. He has authored or coauthored around different journal papers and conference papers. His research interests include machine learning, Deep learning, Internet of Things and others.