Moyeenudin, H. M. and Anuradha, T. and Niraimathy, K. and Devika, C. and Baby, P. Vinitha and Anand A., Jose (2024) Artificial Intelligence based Sustainable Parking Slot Alerting System with Cloud Platform. In: 2024 1st International Conference on Sustainability and Technological Advancements in Engineering Domain (SUSTAINED), Faridabad, India.
Full text not available from this repository. (Request a copy)Abstract
With improvements of the Internet of Things (IoT), Artificial Intelligence (AI), aspect computing and different communique technology have paved manner for the trouble via way of means of processing the records regionally at the threshold of a surveillance device. In this, aspect computing is used for detecting sustainable parking occupancy from the actual video. The device pipeline is cautiously intended with the attention of suppleness, online investigation, records communication, recognition correctness, and device dependability. It allows AI at the threshold via way of means of enforcing more advantageous You Only Look Once (YOLO) and some greater algorithms are evolved both regionally at the threshold of the device or at the centralized records server which is concentrated mostly on desirable device performance and accuracy. The pervasive presence of clever smartphones encourages customers to decide on cell software which acts as the primary solution for improved sustainable development. The investigational outcome is talented that the very last recognition technique attains over 97% accurateness in real-international situations. The proposed device that is based on aspect computing and AI offers the right answer for detecting the vacant parking areas with greater accuracy will explore the benefits of Sustainable Development Goals (SDG) for infrastructure development..
Item Type: | Conference or Workshop Item (Paper) |
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Subjects: | Computer Science Engineering > Artificial Intelligence |
Domains: | Hotel and Catering Management |
Depositing User: | Mr IR Admin |
Date Deposited: | 28 Aug 2025 10:19 |
Last Modified: | 28 Aug 2025 10:19 |
URI: | https://ir.vistas.ac.in/id/eprint/10932 |