A Secured Manhole Management System Using IoT and Machine Learning

Krishnan, R. Santhana; Sangeetha, A.; Kumari, D. Abitha; Nandhini, N.; Karpagarajesh, G.; Narayanan, K. Lakshmi; Robinson, Yohan

doi:10.1007/978-3-030-90119-6_3

Cited by 10 publications

(1 citation statement)

References 18 publications

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“…As per [5] The gadget recognizes any development of the sewer vent cover and tells the Metropolitan Enterprise. Along these lines, the condition of the sewers is followed consistently, and when a crisis emerges, the Civil Organization is told of the nature and area of the issue inside the sewage organization.…”

Section: Literature Surveymentioning

confidence: 99%

Smart Manhole Managing and Monitoring System Using IOT

Sharma

2023

IJRASET

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A smart city is the future goal for humanity to have cleaner and better amenities. When creating a smart city, smart subsurface infrastructure is a crucial component to consider. Monitoring the drainage system is critical to keeping the city clean and healthy. Because human monitoring is ineffective, drainage problems are handled slowly and take longer to resolve. The technology is designed to plot the co-ordinates of the manholes using GPS.The proposed approach is low-cost and requires little maintenance. The GPS will refresh the information every 5 minutes. When crossing a manhole, the driver is alerted that a manhole is ahead, allowing them to avoid it. The system employs a machine learning algorithm based on Q-Learning to calculate each state. If any of those parameters changes abruptly, the system connects to the admin office and notifies the situation via message wherever it has been posted. This study would be tremendously beneficial to society in terms of manhole maintenance. Implement a Reinforcement Learning algorithm, such as Q-Learning, that is based on reward and policy. A test data set will be used to assess the performance of the Q learning model.

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Section: Literature Surveymentioning

confidence: 99%