Objective.
The objective of the proposed AI module, LitterWatch, is to enhance the efficiency and accuracy of monitoring public trash bins by automating the detection of littering activities. This system aims to reduce the burden on staff, improve response times, and increase the overall cleanliness of public areas.
Our Process.
LitterWatch integrates advanced AI technology with existing camera infrastructure to create a comprehensive monitoring system. The solution processes video feeds in real-time, automatically detecting and reporting littering incidents while maintaining data security and privacy compliance.
Current Scenario.
Currently, staff members are responsible for monitoring multiple camera feeds in real-time to detect instances of littering. This manual process is labor-intensive, prone to human error, and can lead to delayed responses. Staff must divide their attention across several screens, making it challenging to catch every instance of littering. As a result, some littering activities go unnoticed, and public areas can become untidy, negatively impacting the environment and public perception.
02
Proposed Transformation
Proposed Transformation.
The implementation of LitterWatch will transform the current monitoring process by introducing an AI-powered system capable of automatically identifying and recording instances of littering.
1
Automate Detection
Use computer vision algorithms to detect accidents, breakdowns, hazardous driving, and traffic congestion across the monitored network.
2
Alert Staff
Immediately notify staff members when littering is detected, enabling them to respond quickly and address the issue effectively.
3
Collect Evidence
Record footage of the littering event, capturing clear images of the perpetrator for use in enforcement and awareness campaigns.
4
Reduce Workload
Reduce the need for constant manual monitoring, freeing staff to focus on enforcement and community engagement.
5
Enhance Accuracy
Minimize human error and ensure that every instance of littering is promptly detected and addressed effectively for improved management.
6
Data Analytics
Provide valuable data on littering patterns, helping the government implement targeted interventions and policies.
By adopting LitterWatch, the government can significantly improve the cleanliness of public areas, increase the effectiveness of litter enforcement, and ultimately create a cleaner, more pleasant environment for the community.