Green Communication with Object Detection for Energy-Efficient Smart Shopping Carts
Sadaf Hussain, Amna Sajid, Tanweer Sohail, Muhammad Nauman Aslam, Muhammad Shamrooz Aslam · Mehran University Research Journal of Engineering and Technology · 2025
With an emphasis on reducing environmental impact and increasing energy efficiency, this research investigates how green communication principles might improve the performance of Internet of Things (IoT) devices. Given the rising importance of green communication in solving environmental problems, including CO2 emissions and pollution, the study explores the fundamental ideas, operational cycles, advantages, and uses of both IoT and green IoT. For retail settings, a smart shopping cart system has been developed to show how these ideas may be applied practically. Through green RFID technology, the system allows for quick item scanning and eliminates standard barcode readers, hence saving energy. Furthermore, a YOLOv9 object detection model is included to help precisely recognize and monitor items in real-time, therefore smoothing personalized suggestions, stock control, and loss reduction. By reducing energy consumption, reducing waste, and maximizing resource use, this combined strategy not only improves the user experience by streamlining the checkout process and providing useful product information but also supports a more sustainable retail system. The system emphasizes the possibility of using sophisticated technology, including RFID and computer vision, together with green communication ideas to create unique and environmentally friendly IoT applications. Future research can investigate edge computing applications, including more green technologies, and broaden the system's uses in several different retail and IoT sectors.