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dc.contributor.author | Chatni, Muhammad Furqan Reg # 57123 | |
dc.contributor.author | Rehman, Muhammad Abdul Reg # 57088 | |
dc.contributor.author | Khan, Daniya Anis Reg # 57118 | |
dc.contributor.author | Imtiaz, Muhammad Faisal 57329 | |
dc.date.accessioned | 2023-05-16T06:34:18Z | |
dc.date.available | 2023-05-16T06:34:18Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://hdl.handle.net/123456789/15445 | |
dc.description | Supervised by Engr. Khadija Jalal | en_US |
dc.description.abstract | The recent development in railway inspection, monitoring, and tracking has advanced throughout the globe. Several countries like China and Japan have already introduced Artificial intelligence to their safety protocols in preventing railway accidents one of these is “Tunnel Fox” an autonomous vehicle for railway inspection. Talking about the Railway industry in Pakistan. Pakistan has faced 27 major accidents over the past 20 years, which were all caused by derailments. The technology available in Pakistan has just started to develop but has not reached the level existing elsewhere. We are aiming to introduce AI monitoring to the Railway inspection department. Real-time monitoring of defected tracks. We have made an Electric Cart which is powered by a solar panel which charges the battery through which DC motor runs and electric vehicle moves. It is equipped with a camera which detects track anomalies which are being processed via an AI computer. The technology can precisely and cost-effectively locate an operational train's position and other parameters. This project aims to create and set out a economical and intelligent full-fledged wireless-based Railway Track Detection System to prevent railway accidents. It can help discover fractures and reduce the likelihood of disasters. The system's efficiency can be guaranteed because it will be automated and will require little operator intervention. This system, on the other hand, has difficulty identifying an inner break in the railway track. In the long run, the concept might be utilized on a large scale to promote higher train track safety criteria and provide adequate testing infrastructure to meet the requirement. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Bahria University Karachi Campus | en_US |
dc.relation.ispartofseries | BEE;MFN BEE 111 | |
dc.title | SOLAR POWERED WIRELESS RAIL TRACK MONITORING SYSTEM | en_US |
dc.type | Project Reports | en_US |