Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
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Brac University
2023
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| Rochtain ar líne: | http://hdl.handle.net/10361/19370 |
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10361-193702023-08-09T21:02:03Z Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions Imon, Imran Hossain Authro, Arnab Saha Akter, Joya Safina, Suzhat Neha, Namreen Nayeem Chakrabarty, Amitabha Rabiul Alam, Md. Golam Department of Computer Science and Engineering, Brac University IoT Smart city 5G Garbage management system Smart cities. Artificial intelligence. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 42-44). In smart cities, the volume of data collected by IoT-based sensors is rapidly in creasing. These devices are networked and provide information about how humans utilize them together and independently, as well as how they could be improved. Ev ery individual and business generates waste, but its disposal must be controlled to prevent dangers to public health and the environment. In order to develop sustain able and habitable cities, efficient waste management systems must be implemented. In this situation, recycling is an effective waste management strategy that can be adopted. To ensure the effectiveness of a recycling program, cities and communities must make waste management services easily available. Waste management entails the collection, transportation, and disposal of sewage, rubbish, and other types of waste. Some have postulated that a cognitive network of the fifth generation could contribute greatly to the overall enhancement of IoT system functionality. Today, solid waste is one of the most pressing issues on a global scale, as poor rubbish disposal from villages, towns, and cities has a negative impact on the local popula tion and is the root cause of new diseases. Consequently, technologically-advanced trash management is a pressing matter. In the existing traditional system, garbage monitoring and disposal are performed by humans, which is cumbersome; thus, by incorporating IoT into the traditional system, garbage bin monitoring will be simpli fied. In this study, we investigate the Internet of Things and propose an IoT-based architecture for a Smart Waste Management System in a smart city. Our purpose is to demonstrate how IoT may be utilized to handle and manage smart city waste while accounting for scale and adaptability challenges. The suggested system em ploys ultrasonic sensors to detect the level of trash in the bin and communicate the status of the waste to the bin. Using global system for mobile (GSM), the server will notify the appropriate individuals (driver of garbage collection vehicle) via SMS and GPS location. The driver will gather waste and update the server accordingly. The proposed trash management system is vastly superior to the waste management systems currently employed in its industry since it employs significantly less work ers to fulfill its goals, prevents rubbish spills, reduces processing times and costs, and is entirely automated. Our suggested model can accurately track the status of garbage containers with a 91% success rate, while waste disposal accuracy is 89%. In addition, we investigate the vast array of potential technical applications in a ”smart city,” including ”smart houses,” ”smart buildings,” ”smart industries,” etc. Imran Hossain Imon Arnab Saha Authro Joya Akter Suzhat Safina Namreen Nayeem Neha B. Computer Science and Engineering 2023-08-09T08:21:03Z 2023-08-09T08:21:03Z 2023 2023-01 Thesis ID: 19101277 ID: 19101017 ID: 19101027 ID: 19101484 ID: 19101191 http://hdl.handle.net/10361/19370 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 44 pages application/pdf Brac University |
| institution |
Brac University |
| collection |
Institutional Repository |
| language |
English |
| topic |
IoT Smart city 5G Garbage management system Smart cities. Artificial intelligence. |
| spellingShingle |
IoT Smart city 5G Garbage management system Smart cities. Artificial intelligence. Imon, Imran Hossain Authro, Arnab Saha Akter, Joya Safina, Suzhat Neha, Namreen Nayeem Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions |
| description |
This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. |
| author2 |
Chakrabarty, Amitabha |
| author_facet |
Chakrabarty, Amitabha Imon, Imran Hossain Authro, Arnab Saha Akter, Joya Safina, Suzhat Neha, Namreen Nayeem |
| format |
Thesis |
| author |
Imon, Imran Hossain Authro, Arnab Saha Akter, Joya Safina, Suzhat Neha, Namreen Nayeem |
| author_sort |
Imon, Imran Hossain |
| title |
Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions |
| title_short |
Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions |
| title_full |
Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions |
| title_fullStr |
Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions |
| title_full_unstemmed |
Smart waste management systems for sustainable urban life based on IoT for scalable IoT-based smart city solutions |
| title_sort |
smart waste management systems for sustainable urban life based on iot for scalable iot-based smart city solutions |
| publisher |
Brac University |
| publishDate |
2023 |
| url |
http://hdl.handle.net/10361/19370 |
| work_keys_str_mv |
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| _version_ |
1814308561620041728 |