SmartPit: IoT Driven Manhole Maintenance for Enhanced Human Safety

Manholes, a key element of urban infrastructure, are typically monitored using traditional techniques that lack real-time data acquisition, posing risks for both workers and prepared pedestrians. In this paper, we describe SmartPit, an IoT-based smart supervising system aimed to protect humans by detecting irregularities in manholes and automating maintenance processes. It uses a combination of sensors, edge computing, and cloud-based analytics to monitor important parameters like gas levels, water accumulation, structural integrity, and unauthorized access. Predictive maintenance also finds a supporter in SmartPit which uses Twin support vector machine (TSVM) algorithm to prevent accidental failures and minimize response time. Moreover, with the ability to send real-time alerts and automate decision-making processes, machine learning allows for proactive interventions, reducing operational downtime and maintaining public safety. The proposed system is accurate and reliable, which can be a scalable solution for smart cities. Future work consists of AI-based analytics for better fault forecasting and its incorporation with city digital twins.