Smart Waste Management System using IOE(SWaMS)

Project Title

Smart Waste Management System using IOE(SWaMS)

Project Area of Specialization Internet of ThingsProject Summary

Waste disposal and removal management is one of the core concerns of modern age. Every locality has an issue of efficient and effective garbage collection. Large societies produce large amount of garbage and the delays in removal, cause potential diseases. The removal method currently utilized by Municipal Corporations is FIFO based and is inefficient, depending largely on human ingenuity.

Furthermore, there is no way to identify fill level of a garbage can as well as classify hazard level without manual interaction. Smart Waste Management System Using IoE (SWaMS) envisages to provide real-time status of garbage can based on a Bayesian based classifier. 

Smart waste management system is a three-fold system. In the first phase, smart garbage cans are developed. This includes adding an array of sensors connected with an Arduino unit. These sensors include GPS, temperature, fill sensors, co sensor, weight sensors, etc. Data from each sensor is gathered and uploaded over the cloud.

In the second phase, data collected from the garbage cans is used to classify hazard level using Bayesian learning. Data from all the garbage cans is classified based on history information and a prioritized task list is generated. An administrator can further utilize data analytics at the cloud end on the gathered data to generate data insights.

In the third phase the priority list is used to mark garbage cans on an overlay using google maps. A truck driver can view it on an available mobile device. An optimal path is generated and displayed on the driver’s app as a task list. The task after completion by the driver are then updated via the app.

The potential of this system not only saves fuel spent in waste removal but also provides smart garbage cans and paves the way forward for data insights.

Project Objectives

SWaMS envisages to establish an efficient priority based optimized path for garbage collection. This effectively saves fuel that is wasted in preset paths. Furthermore, utilizing IoT community garbage cans would be converted to smarter versions that lead to analytics. The increase in functionality not only would reduce maintenance cost but would open avenues for revenue generation as well while providing green environment.

Project Implementation Method

SWaMS is intended to be developed as an Object-Oriented system following a bottom-up approach. The system will be developed in the following stages: -

Stage 1: Development of Smart Trash Cans: In this stage the available trash cans will be converted to a smart version by installing and configuring sensors. The sensors will be connected to associated Arduino units that will upload data over the cloud. Data upload can be carried out using GSM or Wi-Fi depending on availability.

Stage 2: Development of Smart Waste Manager and Analytics Module: This module will be developed as a Java Applet to allow web access.  This module stores collected data of each Smart Trash Can on the server

Stage 3: Development of Driver and Resident Apps: In this stage apps for Driver of Garbage Disposal Unit as well as Residents will be made. Residents can track complaints and view statistics of nearby trash cans. A driver can view task list generated by system and update task statuses.

Figure: Block Diagram of SWaMS

Benefits of the Project

SWaMS allows our team to establish IoE to implement Industry 4.0 vision which is a contemporary trendsetter. The solution developed would not only provide a greener environment but could also be exported to developing as well as developed countries, thus establishing Made in Pakistan as a futuristic brand.

Technical Details of Final Deliverable

The Smart Waste Management System is divided into four main components. Trash Can Component collect data from a microcontroller (Arduino Uno). A Cloud Based Component produces statistics and generate priority list. The Driver App would let a driver check the priority list which is plotted on the map and update task status. The Resident App would let the user check the task status to identify the trash can is emptied on their schedule timings or not. The conceptual diagram of the proposed system is shown in Figure 1. There are four major components of this system that are described in Table 1.

Table 1: Description of Major Components of SWaMS

Component	Description
Smart Trash Can	A normal trashcan is converted to a smart one by attaching a sensor array activated via Arduino to it. The sensors include Temperature sensor, fill sensor, CO sensor, smoke sensor, weights sensor and GPS
Smart Waste Manager and Analytics Module	The data collected at a Smart Trash Can is updated on Waste Management Server. This data is stored on a private cloud. The data is used to identify hazard level of a trash can via Bayesian Learning. A priority list is generated which is then shared with the Garbage Collection Unit. Furthermore, an administrator can use this data to draw analytics.
Garbage Collection App	The driver of a Garbage Collection Unit can receive prioritized task list for waste removal. Remove the waste and update task list.
Resident App	A resident can view the statuses and be informed on the current situation of nearby trash cans.

Component

Smart Trash Can

Smart Waste Manager and Analytics Module

Garbage Collection App

Resident App

Final Deliverable of the Project HW/SW integrated systemCore Industry OthersOther Industries IT , Transportation , Health Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI), Cloud InfrastructureSustainable Development Goals Good Health and Well-Being for People, Clean Water and Sanitation, Sustainable Cities and Communities, Climate ActionRequired Resources

Elapsed time in (days or weeks or month or quarter) since start of the project	Milestone	Deliverable
Month 1	Idea planning and evaluation	Idea Registration Form
Month 2	Requirements and Design	SRS Chapter 1 and 2
Month 3	SRS Document	SRS Document
Month 4	Hardware Acquisition and Testing	Ultrasonic and Temperature Sensor working module
Month 5	Dashboard Interfaces and Hardware Integration	Interface for bin priority list
Month 6	Smoke Sensor and Weight Sensor Integration	Hardware Integration and Data Acquisition
Month 7	APIs Integration	Google Map and Location APIs integration to show map and places
Month 8	Integration of GSM Module / WiFi Module	Testing of GSM/WiFI Module
Month 9	Addition of Analytics to Dashboard	Admin Dashboard with live sensor data and analytics
Month 10	Testing	Testing of complete project