Smart Dustbins: Transforming Waste Management in Smart Cities

Abstract

In light of India's groundbreaking smart city project, it is imperative to revolutionize the waste collection system for these intelligent urban centers. To accomplish this, ensuring convenient accessibility to garbage disposal points and implementing an optimized collection process are vital for efficient resource utilization in terms of time and fuel.

Introduction

 

Many urban cities and towns in India suffer from inadequately designed systems for proper garbage disposal and collection. Moreover, the rapid urbanization is exerting immense pressure on the existing infrastructure, which is unable to keep up with the pace of expansion. To meet the demands of the government's visionary smart city initiative, which leverages IT-enabled solutions, it becomes crucial to establish a cleaner environment. Our proposed system presents an IT-driven solution that enhances garbage collection efficiency, streamlines disposal planning, and generates comprehensive data on garbage generation. The system effectively addresses three pivotal challenges:

 

1) Enhancing accessibility to public dustbins for efficient garbage disposal.

 

2) Optimizing time and fuel consumption through an efficient collection process.

 

3) Collecting data to assess the volume of garbage generated by cities, facilitating informed disposal planning.

 

Description

 

Our proposed system consists of three layers:

 

1) Dustbin Layer:

This layer incorporates internet and Wi-Fi-enabled dustbins equipped with advanced sensors. These sensors accurately monitor the fill status of the dustbins and periodically transmit the data, including GPS location, to the server.

 

2) Server Layer:

The server collects and processes information regarding the fill status and location of the dustbins. It promptly responds to client queries, providing the nearest dustbin location and offering detailed directions for access.

 

3) Client Layer:

Clients can conveniently request information about the nearest IT-enabled dustbin location from the server using a dedicated mobile application.

Working Principle of an Intelligent Dustbin

 

To determine the fill status of a dustbin, we employ the following formula, where X represents the fill status, T denotes the time duration between wave generation and reception, and C symbolizes the speed of light:

 

X = L - (CT)/2

 

Likewise, the percentage of fill-up is calculated using the following formula:

 

P = (X/L) * 100

 

It is assumed that the wave path is almost vertical.

Implementation

 

To optimize the garbage collection process from these dustbins, we propose the utilization of the following scheduling algorithms:

 

1) Fixed Scheduling:

This approach involves establishing a predetermined collection interval, such as every three days. The Traveling Salesman Problem algorithm can be employed to plan the collection route effectively.

 

2) Priority Scheduling:

Dustbins are prioritized for collection based on their decreasing fill status. For instance, if we have three dustbins with fill statuses of 92%, 80%, and 96%, the collection order would be 96%, 92%, and then 80%.

 

3) Average Threshold Scheduling:

In this approach, we calculate the average fill status of all dustbins. If the average exceeds a predefined threshold, such as 70%, the collection process is scheduled. Within this scheduling framework, the collection order can be determined either by employing the Priority Scheduling or the Traveling Salesman Problem approach.

 

4) Full Dustbin Capacity Utilization Scheduling:

Collection is carried out only when all dustbins have reached their full capacity. Once again, the Traveling Salesman Problem algorithm can be utilized to plan an optimal route.

Advantages

 

1. Our system ensures enhanced accessibility to dustbins, thereby significantly improving the overall waste management process.

 

2. In the event of a dustbin being relocated, our system automatically updates the server with the new GPS location, ensuring accurate information retrieval.

 

3. By implementing effective route planning, our system optimizes fuel consumption and saves valuable time. The Traveling Salesman Problem algorithm can be employed to accomplish this goal.

 

4. Through reduced fuel consumption, particularly of diesel and petrol, our system actively contributes to minimizing pollution and promoting a cleaner environment.

 

5. The data provided by our IT-enabled dustbins facilitates better planning and design of the waste collection process. Monthly estimates of current garbage disposal levels can be obtained, empowering decision-makers with valuable insights.

 

Conclusion

 

One notable advantage of our system lies in the government's ability to leverage garbage generation statistics for policy and program design. By effectively implementing this system, we can make significant strides towards cleaner, greener cities, thereby transforming the vision of smart cities into a tangible reality.

 

Hashtag/Keyword/Labels:

#SmartDustbins #SmartCities #GarbageCollection #WasteManagement #Efficiency #Sustainability

 

References/Resources:

 

1. Michael Batty, Kay Axhausen, et al., "Smart Cities of the Future," UCL Centre for Advanced Spatial Analysis on working paper series.

2. Narayan Sharma, Nirman Singha, Tanmoy Dutta, "Smart Bin Implementation for Smart Cities," International Journal of Scientific & Engineering Research.

3. "Smart Cities" available at www.smartcities.gov.in.

 

For more such Seminar articles click index – Computer Science Seminar Articles list-2023.

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…till next post, bye-bye and take care.