Spitting and Littering Detection System through Deep Learning
Year: 2025
Type: article
Abstract: All levels of government are currently working around the clock to contain the Coronavirus.Consequently, the system's primary objective is to employ cutting-edge computer technology to curb thespread of infectious diseases such as the Coronavirus by enforcing a severe ban on public spitting throughthe use of real-time drone-based surveillance systems. Spitting is the primary vector for the virus'smaximum replication. A combination of closed-circuit television and unmanned aerial vehicles (UAVs)will monitor public spaces and record any actions taking place there in real time. Following transmissionover the Cloud, the data will be evaluated for the presence of public spitting. The local authorities willhave access to the results through a web/mobile interface. The person can thereafter face punishment fromthe authorities. A more effective management and monitoring of public spitting can be achieved with thehelp of this approach. Computer vision, namely Convolutional Neural Networks and Decision Making, hasbeen employed in the system's design to accomplish the task of spitting and garbage littering detection.
Author: Mr.Vasim Tamboli, Vikhe Bhakti, Shirsath Ishwari, Kakade Shruti
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W6911887131
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