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Trash-Pot : Waste Management System for Handle Garbage � Collection Process with Service Rating System. �

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  • Municipal solid waste (MSW) management is regarded as a challenging matter for contemporary cities due to quick growth in the amount of waste, high waste collection costs , limited treatment capacities  and environmental problems [1].

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  • Increasing waste generation has become a significant challenge in developing countries due to unprecedented population growth and urbanization. [10]

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  • This paper presents a case study conducted in a municipality in Sri Lanka. Officials, More than 300 householders of different income groups and landfill operators were interviewed to examine current practices and environmental problems [6]

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INTRODUCTION

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The main objective of the project is to design and develop a “Waste Management System for handling garbage collection process for efficiency ” as a web-based system which will assist in predicting illegal waste hotspots, scheduling waste collection process, identify filled up garbage bins and and rating employees for their service.

RESEARCH OBJECTIVES

MAIN

OBJECTIVE

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Develop a software component to provide the city council with a map to identify predicted illegal waste hotspots based on the location type using predictive analysis in data-driven approach.

Trash Pot-Hub

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Develop a software component to create a dynamic schedule for manage overall garbage collection process with in given geographical area.

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Develop an IoT based software component to indicate the level of garbage bins located around housing complexes to inform the council and identify waste generation in those area.

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Identify the factors, design and develop an algorithm  to evaluate the services of the garbage collectors.

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schedule

Garbage collection

Illegal Garbage Dumps

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System Diagram

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IT19207896 BADDEGAMA D.T.

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  • Specific Objective

Develop a map that can be used to display predicted garbage dumps based on the location type.

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  • Sub Objectives
  • Data Preprocessing
          • Data collection and processing for features
          • Identifying the most frequently occurring location types in the dataset
  • Model Training
  • Develop a city map to plot area
  • Provide an option to filter the map by area name.
  • Spot the predicted garbage dumps according to the selected location type.

Specific and Sub Objective

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Research Questions

  • How can illegal waste dumps be predicted?
  • How to identify location types that can occur garbage dump sites?
  • How to display the predicted illegal waste dumps in a map based on the location type?
  • How to notify the garbage collectors about the hotspots?

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High –level System Diagram

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Methodology

    • Data Preprocessing

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  • Data collection and processing for features :
    • Collect Data from the District 3-Colombo Municipal Council
      • Illegal dump records around the District 3
      • Legal Dump sites in District 3
    • Processing of data for features
          • location type
        • Ward name (CMC Website)
        • Distance to Nearest Road (Google map )
        • Ward Population (sensors and statistics department sri lanka)
        • Population Density(m^2)
        • Distance to Nearest Venue(m) (Google map )
        • Number of Venues (Google map )
        • Average Distance of Venues
        • Lable (1-Illegal , 0 - Legal)
        • Status (Illegal , Legal)

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Completion of the Project

  • Data Preprocessing– Completed

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  • Data collection and processing for features

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Methodology

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  • Identifying the most frequently occurring location types in the dataset :
    • Using municipal data, we classified the location types of illegal and legal garbage and discovered the most frequently occurring location types in the dataset.
    • The most frequently occurred location types are,
          • Restaurant
          • Shop
          • Religious Places
          • School
          • Office
          • Ground

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Completion of the Project

  • Data Preprocessing– Completed

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  • Identifying the most frequently occurring location types in the dataset

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Methodology

  • Model Training :
    • Implement a k-nearest neighbors (KNN) algorithm classification model
      • Accuracy – 69%

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    • Implement a Random forest algorithm classification model
      • Accuracy – 69%

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Methodology

  • Model Training :
    • Implement a AdaBoost algorithm classification model
        • Accuracy – 83%

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    • Adaboosting Algorithm has chosen an accuracy of 83 %.
    • Train it to classify the location, whether it is an illegal garbage spot or legal garbage spot.
    • Test the model performance using testing data
        • Distance to Nearest Venue(m)
        • Number of Venues
        • Average Distance of Venues
        • Lable (1-Illegal , 0 - Legal)

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Completion of the Project

  • Model Training– Completed

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  • Model Training

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Status: [0] -> Legal dump spot

Status: [1] -> Illegal dump spot

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Requirements

And Future Developments

  • Functional Requirements 

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  • Should have a method to filter the relevant area through the map. 
  • Should have a method to remove the location type.
  • Should have a method to display the garbage dump near the selected location.

 

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  • User Requirements 

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  • CMC Administration: To identify the waste dumps through map.
  • Labors: To aware the details about garbage hotspots

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  • Future Developments
  • Create a map for two selected Colombo districts that shows the predicted illegal garbage spots for location types which derived from the dataset.

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IT19180380 ARIYASENA P.G.H.S

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Specific Objective :

    • Develop a software component to create a dynamic schedule for managing the overall garbage collection process.

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Sub Objectives :

    • Develop a method to detect the public events which are published on selected websites to recognize the uninformed events within given geographical area
    • Develop a method to generate weather forecasting report for a day/week according to the weather condition of a selected geographical area.
    • Create a dynamic schedule which can update dynamically according to some selected internal and external factors.

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Specific and Sub Objective

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Research Questions

1. How to identify the public events / gatherings which are happening without informing to the CMC , within selected geographical area.

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2. How to create weather forecasting report for identify most suitable time (Morning or Afternoon) for collecting garbage.

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3. How to create a dynamic schedule which can update dynamically according to some selected internal and external factors.

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System Overview Diagram

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Methodology

    • Develop a method to detect the public events which are published on selected websites to recognize the uninformed events within given geographical area.

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  • Recognize the uninformed public events:
    • Find the URL that you want to scrap the details of the events which will be held within a selected geographical area
    • Inspecting the relevant Page.
    • Find the events that needed to extract.
    • Write the code to create the crapper and run the code to extract the relevant data to the system.
    • Store the filtered data in a required format
    • Selenium , Beautiful Soup and Pandas library.

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Completion of the Project

  • Recognize the uninformed public events in Colombo area using web scrapping – 90%
  • 10Times.com Meetup.com

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Methodology

    • Develop a method to generate weather forecasting report for a day/week according to the weather condition of a selected geographical area - 90%.

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    • PIL: this model is used to handle Json files and comes built in with python.
    • Requests: It is used for making HTTP requests to a specified URL
    • use Open Weather Map API to get weather data, including current weather data, forecast , and historical data.

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Completion of the Project

  • Develop a method to generate weather forecasting report for a day/week according to the weather condition of a selected geographical area – 90%

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Completion of the Project

  • Internal Factors : -

Employee Leave Management – 90%

Vehicle Condition Monitoring – 70%

Route Condition Monitoring – 70 %

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Completion of the Project

  • Create a dynamic schedule which can update dynamically according to some selected internal and external factors - In Progress

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Functional Requirements

    • Should have functionality to inform the condition of the vehicle to the system in a emergency situation.
    • Should have functionality to get the details about drivers and assistants leave plan.
    • Should have a functionality to inform about the event details to the system.
    • Should have a functionality to inform the condition of the route to the system in an emergency situation.

User Requirements

  • Municipal Council and Customers :

– Ability to view the dynamic schedule of particular week.

Customers -  Ability to collect extra rounds of garbage.

Future Development

  • Development of the dynamic schedule by considering above mentioned factors

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Requirements

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IT19155494 WIJETHUNGA S.H.

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Specific and Sub Objective

Main Objective

  • Develop an IoT-based smart bin to identify the garbage level of the bin, lock the bin when it has filled up and unlock it and notify the authority about the status of the bin and its location.

Sub Objectives

  • Develop a feature to open and close the lid automatically.
  • Develop the smart bin to identify the garbage level and lock the bin when it has filled up.
  • Develop a feature to lock the bin whenever it’s going to fall before filling up.
  • Develop a feature to unlock the bin.
  • Develop a platform to display the status of the bin and its location to the authority.

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Research Questions

  • What are the issues in the current garbage bin clearance process?
  • How can IoT be used in a smart garbage monitoring system?
  • How to notify the municipal council about filled-up garbage bins to be cleared with help of a smart bin?

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System Overview Diagram

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Methodology

  • Develop a feature to open and close the lid automatically.

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  • Open and Close the lid automatically
      • Check the front distance of an object using Ultrasonic Sensors.
        • Garbage level needs to be greater than 10cm and front distance needs

to be less than 30cm.

      • Open when the bin is not filled up and wait for a two seconds

and close using Servo Motors.

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Completion of the Project

  • Open and Close the lid automatically - Completed

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Methodology

  • Develop the smart bin to identify the garbage level and lock the bin when it has filled up.

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  • Identify levels and indicate with LEDs
      • Check garbage levels using Ultrasonic Sensors.
      • Indicate each level using LEDs.

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  • Lock the bin when it has filled up.
      • Check whether the bin is filled up.
      • Lock the bin using the lid lock.

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Completion of the Project

  • Identify levels and indicate with LED indicators - Completed

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Level 1 Level 2 Level 3

20cm < level 1< 30cm 10cm< level 2< 30cm level 3 < 10cm

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Completion of the Project

  • Lock the bin when it has filled up - Completed

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Indicators

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Lid Lock

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Methodology

  • Develop a feature to lock the bin whenever it’s going to fall.

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  • Identify the position of the bin using the ADXL345 accelerometer.
      • Check the Accelerometer values and get values.

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Methodology

  • Develop a feature to lock the bin whenever it’s going to fall.

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      • According to the values got for x_out and y_out check whether the bin is going to fall or not and lock the bin.

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Completion of the Project

  • Develop a feature to lock the bin whenever it’s going to fall - Completed

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The bin is half-filled up and in a normal position The bin is half-filled up and going to fall

-Bin is unlocked- -Bin is locked-

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  • Functional Requirements
  • Should have a method to open and close the lid automatically.
  • Should have a way to identify levels of garbage and indicate them.
  • Should have a way to lock and unlock the bin on relevant requirements
  • Should have a way to transmit data to the relevant authority.

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  • User Requirements
  • Users – Ability to leave garbage in an easy way.
  • Municipal council – Ability to identify garbage bins’ levels and filled up bins’ locations.

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  • Future Developments
  • Develop a feature to unlock the bin
  • Develop a platform to display the status of the bin and its location to the authority.

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Requirements

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IT19244594 BOWATHTHA B.L.D.M.

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  • Specific Objective

Identify the factors, design and develop an service rating algorithm to evaluate the services of the garbage collectors.

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  • Sub Objectives
  • To identify the key factors for evaluating garbage collection services.
  • To develop a rating algorithm for evaluating garbage collectors’ performance and productivity.
  • To develop a star rating prediction for overall service feedback.
  • To implement a method to identify negative or positive feedback and visualizing.
  • To develop rating scale for overall area citizens ’supportiveness using area feedback.

Specific and Sub Objective

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Research Questions

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  • How to identify key factors to evaluate garbage collection service?

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  • How to identify and categorize negative and positive feedback?

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  • How is overall garbage collection service in those areas?

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  • How to check the percentage of positive feedback for each garbage collector?

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  • How to check for supportiveness of citizens in those area?

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System Overview Diagram

System Overview Diagram

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Methodology

  • Identify the key factors for evaluating garbage collection services.

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    • Data Collection

Collect Data from the citizens, environment policies and environment clubs in Division 3-Colombo Municipal Council

    • Using pandas and numpy and matplotlib.pyplot libraries for identify the key factors.

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Completion of the Project

  • Identify the key factors for evaluating garbage collection services– 90% Completed

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Completion of the Project

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  • Using Matplotlib library for data visualization

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Methodology

To implement a method to identify negative or positive feedback and visualizing–

    • To implement a method to identify negative or positive feedback using NLP
    • Using pandas,numpy,seaborn and matplotlib.pyplot libraries for categorize feedback and visualizing parts.
    • Using word cloud to visual representations of words that give greater prominence to words that appear more frequently. 

Dataset

Data Preprocessing

Data Analysis

Classify Polarity

Data Cleaning

Reprocessing Text in Numeric Form

Split Dataset

Build Model

Cleaned Data

Visualized Data

Train & Test Dataset

Positive & Negative

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Methodology

IT19244594 | Bowaththa B.L.D.M | 2022-035

Text Preprocessing and Data Cleaning

  1. Begin by removing the html tags.
  2. Remove any punctuations or limited set of special characters.
  3. Check if the word is made up of English letters and is not alpha-numeric.
  4. Check to see if the length of the word is greater than 2 (as it was researched that there is no adjective in 2-letters).
  5. Convert the word to lowercase.
  6. Remove Stop words
  7. Finally Snowball Stemming the word

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Original Reviews

Dropping stop words & steaming

Dropping Special Characters

Converting to small-case

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Completion of the Project

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  • To implement a method to identify negative or positive feedback and visualizing– 90% Completed

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  • ['compound'] >= 0 Positive
  • ['compound'] < 0 Negative

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Ex:

  • Compound = 0.9453

Sentiment : Positive

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  • Compound = -0.5455

Sentiment : Negative

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Methodology

IT19244594 | Bowaththa B.L.D.M | 2022-035

  • Develop a star rating prediction for overall service feedback.

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  • Using pandas,numpy,seaborn,re and matplotlib.pyplot libraries for star rating prediction algorithom.
  • Using HFIDF and Linear SVM algorithm
  • Data Pre-processing : Using the star rating prediction algorithm, eliminate punctuations and special characters, remove stop words, tokenization, lemmatize the text
  • Dataset :Create dataset collect data from the citizens in Colombo.

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Completion of the Project

  • Develop a star rating prediction for overall service feedback.– 90% Completed

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Input:

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Completion of the Project

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Develop a star rating prediction for overall service feedback.– 90% Completed

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  • Labor Registration(Evaluate garbage collectors' performance)– In Progress

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Labor Registration Dashboard(Admin)

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Display no of areas, no of labors ,no of roads(locations) and no of registered citizens

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Functional Requirements

    • Evaluate garbage collectors’ performance.
    • Categorize feedback and visualize.
    • Evaluate overall garbage collection service in specific areas.
    • Rating the supportiveness of citizens.

Non-functional Requirements

    • Efficiency and performance of the system
    • Ensuring system availability and accuracy

Future Development​

  • To develop a rating algorithm for evaluating garbage collectors’ performance To develop rating scale for overall area citizens ’supportiveness using area feedback.

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Requirements

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  • Once the system has been successfully tested, system will be fully migrated, and the service will be introduced to users.
  • Introducing the smart garbage monitoring bin as a value-added system for the society.
  • Targeted Users,
      • The Municipal Council
      • External Users
  • Once the Municipal Council register to the service they can identify the highlighted unit features.

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Commercialization

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  • Method to show the live locations of the garbage hotspots.
  • Method to submit customer complains.
  • Method to allocate extra rounds of garbage collection based on requests.
  • Method to trade the collected garbage for commercialize recycling organizations.
  • Method the report the current trucks and routes conditions in an emergency manner.

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Additional Features

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Gantt Chart

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REFERENCES

Use IEEE referencing format

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[1] Sun, Nayseang; Chungpaibulpatana, Supachart (2017). Development of an Appropriate Model for Forecasting Municipal Solid Waste Generation in Bangkok. Energy Procedia, 138(), 907–912. doi:10.1016/j.egypro.2017.10.134

[2] Zhu Minghua; Fan Xiumin; Alberto Rovetta; He Qichang; Federico Vicentini; Liu Bingkai; Alessandro Giusti; Liu Yi (2009). Municipal solid waste management in Pudong New Area, China. , 29(3),12271233. doi:10.1016/j.wasman.2008.07.016 

[3] Akhtar, Mahmuda; Hannan, M A; Basri, Hassan; Scavino, Edgar (2015). SOLID WASTE GENERATION AND COLLECTION EFFICIENCIES: ISSUES AND CHALLENGES. Jurnal Teknologi, 75(11), –. doi:10.11113/jt.v75.5331 

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ITXXXXXXXX | <<Student Name>> | <<Project ID>>

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[4]Zainun, N. Y., Rahman, I. A., & Rothman, R. A. (2016). Mapping Of Construction Waste Illegal Dumping Using Geographical Information System (GIS). IOP Conference Series: Materials Science and Engineering, 160, 012049. doi:10.1088/1757-899x/160/1/012049  

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[5]Glanville, Katharine; Chang, Hsing-Chung (2015). Mapping illegal domestic waste disposal potential to support waste management efforts in Queensland, Australia. International Journal of Geographical Information Science, 29(6), 1042–1058. doi:10.1080/13658816.2015.1008002  

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[6]Bandara, Nilanthi J.G.J.; Hettiaratchi, J. Patrick A. (2010). Environmental impacts with waste disposal practices in a suburban municipality in Sri Lanka. International Journal of Environment and Waste Management, 6(1/2), 107–. doi:10.1504/ijewm.2010.033987

ITXXXXXXXX | <<Student Name>> | <<Project ID>>

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[7]Pavel, Jan; Slavík, Jan (2017). The relationship between competition and efficiency of waste-collection services in the Czech Republic. Local Government Studies, (), 1–22. doi:10.1080/03003930.2017.1411812

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[8]Puche Regaliza, Julio César; Alvear González, Arturo; Aparicio Castillo, Santiago; Arranz Val, Pablo; Lara Ortega, Fernando (2018). Key factors in levels of public satisfaction with urban waste collection in a northern Spain city. Journal of Material Cycles and Waste Management, (), –. doi:10.1007/s10163-018-0713-x

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[9]Jiayuan Wang; Hongping Yuan; Xiangping Kang; Weisheng Lu (2010). Critical success factors for on-site sorting of construction waste: A china study. , 54(11), 931–936. doi:10.1016/j.resconrec.2010.01.012

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[10] Kumar, S. Vinoth; Kumaran, T. Senthil; Kumar, A. Krishna; Mathapati, Mahantesh, “Smart garbage monitoring and clearance system using internet of things”,(2017).

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[11] C. Caruso; A. Colorni; M. Paruccini, “The regional urban solid waste management system: A modelling approach” (1993).

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[12] S. Kanta; S. Jash; H. Nath Saha, “Internet Of Things Based Garbage Monitoring System”, (2017).

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