scholarly journals An IoT Based Efficient Waste Collection System with Smart Bins

2020 ◽  
Author(s):  
Khandaker Foysal Haque ◽  
Rifat Zabin ◽  
Kumar Yelamarthi ◽  
Prasanth Yanambaka ◽  
Ahmed Abdelgawad
Keyword(s):  
Real Time ◽  
Human Life ◽  
Waste Collection ◽  
Real Time Monitoring ◽  
Collection System ◽  
Mount Pleasant ◽  
Human Labor ◽  
Random Location ◽  
Village Life ◽  
The City

<div>Waste collection and management is an integrated</div><div>part of both city and village life. Lack of optimized and efficient waste collection system vastly affect public health and costs more. The prevailing traditional waste collection system is neither optimized nor efficient. Internet of Things (IoT) has been playing a great role in making human life easier by making systems smart, adequate and self sufficient. Thus, this paper proposes an IoT based efficient waste collection system with smart bins. It does real-time monitoring of the waste bins and determines which bins are to emptied in every cycle of waste collection. The system</div><div>also presents an enhanced navigation system that shows the best route to collect wastes from the selected bins. Four waste bins are assumed in the city of Mount Pleasant, Michigan at random location. The proposed system decreases the travel distance by 30.76% on an average in the assumed scenario, compared to the traditional waste collection system. Thus it reduces the fuel cost and human labor making the system optimized and efficient by enabling real-time monitoring and enhanced navigation.</div>

scholarly journals An IoT Based Efficient Waste Collection System with Smart Bins

2020 ◽  
Author(s):  
Khandaker Foysal Haque ◽  
Rifat Zabin ◽  
Kumar Yelamarthi ◽  
Prasanth Yanambaka ◽  
Ahmed Abdelgawad
Keyword(s):  
Real Time ◽  
Human Life ◽  
Waste Collection ◽  
Real Time Monitoring ◽  
Collection System ◽  
Mount Pleasant ◽  
Human Labor ◽  
Random Location ◽  
Village Life ◽  
The City

<div>Waste collection and management is an integrated</div><div>part of both city and village life. Lack of optimized and efficient waste collection system vastly affect public health and costs more. The prevailing traditional waste collection system is neither optimized nor efficient. Internet of Things (IoT) has been playing a great role in making human life easier by making systems smart, adequate and self sufficient. Thus, this paper proposes an IoT based efficient waste collection system with smart bins. It does real-time monitoring of the waste bins and determines which bins are to emptied in every cycle of waste collection. The system</div><div>also presents an enhanced navigation system that shows the best route to collect wastes from the selected bins. Four waste bins are assumed in the city of Mount Pleasant, Michigan at random location. The proposed system decreases the travel distance by 30.76% on an average in the assumed scenario, compared to the traditional waste collection system. Thus it reduces the fuel cost and human labor making the system optimized and efficient by enabling real-time monitoring and enhanced navigation.</div>

scholarly journals The Potential Benefits Of Real-Time Monitoring Of Combined Sewer Overflows In The City Of Toronto

2021 ◽  
Author(s):  
Romak Kordnejad
Keyword(s):  
Real Time ◽  
Weather Conditions ◽  
Future Research ◽  
Environmental Damage ◽  
Real Time Monitoring ◽  
Combined Sewer Overflows ◽  
Combined Sewer ◽  
Potential Benefits ◽  
Sewer Overflows ◽  
The City

This thesis focuses on the current state of combined sewer overflows (CSO) in the City of Toronto and the potential benefits of utilizing real-time monitoring system to explore options for optimizing current models and reducing future overflows. CSOs containing sanitary and stormwater sewage over spill during wet weather conditions, contaminating bodies of water. Antiquated sewer systems built to support population at the time, no longer have the required capacity to support exponential growth causing environmental damage. Key research findings include exploring the current CSO state in the City of Toronto, remediation plans executed by the City in hopes to reduce CSO and finally concluding the City’s progress to date. Extensive research on CSOs in North American cities has shown initiative towards reducing CSOs while using real-time monitoring systems which can be utilized in the City of Toronto. Future research is required to find effective and efficient ways of implementing such systems.

scholarly journals Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach

Energies ◽  
2020 ◽  
Vol 13 (15) ◽  
pp. 3930 ◽  
Author(s):  
Ayaz Hussain ◽  
Umar Draz ◽  
Tariq Ali ◽  
Saman Tariq ◽  
Muhammad Irfan ◽  
...  
Keyword(s):  
Machine Learning ◽  
Deep Learning ◽  
Real Time ◽  
Air Pollutants ◽  
Garbage Collection ◽  
Air Pollutant ◽  
Real Time Monitoring ◽  
Collection System ◽  
The Real ◽  
The Status

Increasing waste generation has become a significant issue over the globe due to the rapid increase in urbanization and industrialization. In the literature, many issues that have a direct impact on the increase of waste and the improper disposal of waste have been investigated. Most of the existing work in the literature has focused on providing a cost-efficient solution for the monitoring of garbage collection system using the Internet of Things (IoT). Though an IoT-based solution provides the real-time monitoring of a garbage collection system, it is limited to control the spreading of overspill and bad odor blowout gasses. The poor and inadequate disposal of waste produces toxic gases, and radiation in the environment has adverse effects on human health, the greenhouse system, and global warming. While considering the importance of air pollutants, it is imperative to monitor and forecast the concentration of air pollutants in addition to the management of the waste. In this paper, we present and IoT-based smart bin using a machine and deep learning model to manage the disposal of garbage and to forecast the air pollutant present in the surrounding bin environment. The smart bin is connected to an IoT-based server, the Google Cloud Server (GCP), which performs the computation necessary for predicting the status of the bin and for forecasting air quality based on real-time data. We experimented with a traditional model (k-nearest neighbors algorithm (k-NN) and logistic reg) and a non-traditional (long short term memory (LSTM) network-based deep learning) algorithm for the creation of alert messages regarding bin status and forecasting the amount of air pollutant carbon monoxide (CO) present in the air at a specific instance. The recalls of logistic regression and k-NN algorithm is 79% and 83%, respectively, in a real-time testing environment for predicting the status of the bin. The accuracy of modified LSTM and simple LSTM models is 90% and 88%, respectively, to predict the future concentration of gases present in the air. The system resulted in a delay of 4 s in the creation and transmission of the alert message to a sanitary worker. The system provided the real-time monitoring of garbage levels along with notifications from the alert mechanism. The proposed works provide improved accuracy by utilizing machine learning as compared to existing solutions based on simple approaches.

Autonomous Real-Time Monitoring of Crops in Controlled Environment Agriculture

2019 ◽  
Author(s):  
Saba Faryadi ◽  
Mohammadreza Davoodi ◽  
Javad Mohammadpour Velni
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Directed Graphs ◽  
Controlled Environment ◽  
Real Time Monitoring ◽  
Collection System ◽  
Image Processing Algorithm ◽  
Ground Vehicle ◽  
Controlled Environment Agriculture ◽  
And Performance

Abstract In this work, we develop a system that can be used for real-time monitoring of multiple important areas in controlled environment agriculture (and in particular greenhouses) using an autonomous ground vehicle (AGV). To model the greenhouse layout, as well as the tasks that should be accomplished by the AGV, we generate two weighted directed graphs. Based on those graphs, an algorithm is then proposed for finding the optimal (in the sense of traveled distance) trajectory of the vehicle with the goal of precisely monitoring important areas in the greenhouse. Furthermore, a data collection system and image processing algorithm is proposed and implemented so that the vehicle: (i) can capture images and detect changes that have occurred on the crops in real time, and (ii) construct (if needed) a map of the plant rows, when arriving at each one of the important areas. Based on this work, the images can either be stitched onboard the vehicle and then sent to a server or be sent directly to the server and then processed (stitched) there. Both simulation and experimental results are provided to demonstrate the effectiveness and performance of the proposed system.

Door-to-door recyclables collection programmes: Willingness to participate and influential factors with a case study in the city of Xanthi (Greece)

2018 ◽  
Vol 36 (9) ◽  
pp. 760-766 ◽  
Author(s):  
Thomas Tsalis ◽  
Sonia Amarantidou ◽  
Paolo Calabró ◽  
Ioannis Nikolaou ◽  
Dimitrios Komilis
Keyword(s):  
Waste Management ◽  
Influential Factors ◽  
Willingness To Participate ◽  
Waste Collection ◽  
Collection System ◽  
Solid Waste Collection ◽  
Greek City ◽  
Explanatory Variables ◽  
The City

The implementation of a recyclable waste management system is a serious challenge for a society that aims to contribute to sustainability. The first operational step of such system is waste collection. In a number of European countries, the solid waste collection system has changed from the conventional kerbside system to a door-to-door collection. However, this type of waste collection system has not yet been introduced in Greece and its public acceptance prior to potential full implementation needs to be considered. This study aims to investigate the willingness of the residents of a Greek city (Xanthi, Thrace) to change from the existing kerbside collection system and initiate and participate in a door-to-door recyclable waste collection system instead. A questionnaire was designed and distributed randomly to 150 residents of Xanthi and a statistical analysis was then performed to assess the influence of a number of explanatory variables on recycling behaviour and the willingness to participate in a door-to-door collection system. The findings of this study indicate that most of the respondents (72.7%) were willing to participate in a future door-to-door recyclables collection programme in Xanthi. The factors that influenced the respondents’ attitude with regard to such a programme were associated with level of education, their beliefs about the effectiveness of the current recycling system and also their attitudes towards recycling issues in general. Age and religion significantly affected recycling frequency. The survey and statistics presented in this article can be used as a model to assess the behaviour of citizens towards recyclable waste management systems worldwide.

scholarly journals The Potential Benefits Of Real-Time Monitoring Of Combined Sewer Overflows In The City Of Toronto

2021 ◽  
Author(s):  
Romak Kordnejad
Keyword(s):  
Real Time ◽  
Weather Conditions ◽  
Future Research ◽  
Environmental Damage ◽  
Real Time Monitoring ◽  
Combined Sewer Overflows ◽  
Combined Sewer ◽  
Potential Benefits ◽  
Sewer Overflows ◽  
The City

This thesis focuses on the current state of combined sewer overflows (CSO) in the City of Toronto and the potential benefits of utilizing real-time monitoring system to explore options for optimizing current models and reducing future overflows. CSOs containing sanitary and stormwater sewage over spill during wet weather conditions, contaminating bodies of water. Antiquated sewer systems built to support population at the time, no longer have the required capacity to support exponential growth causing environmental damage. Key research findings include exploring the current CSO state in the City of Toronto, remediation plans executed by the City in hopes to reduce CSO and finally concluding the City’s progress to date. Extensive research on CSOs in North American cities has shown initiative towards reducing CSOs while using real-time monitoring systems which can be utilized in the City of Toronto. Future research is required to find effective and efficient ways of implementing such systems.

scholarly journals A Cost-Effective IoT Model for a Smart Sewerage Management System Using Sensors

J ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 356-366
Author(s):  
Jahid Hasan Rony ◽  
Nazmul Karim ◽  
MD. Abdur Rouf ◽  
Md. Monirul Islam ◽  
Jia Uddin ◽  
...  
Keyword(s):  
Real Time ◽  
Monitoring System ◽  
Mobile Communications ◽  
Management System ◽  
Cost Model ◽  
Cost Effective ◽  
Waste Collection ◽  
Real Time Monitoring ◽  
Expansion Process ◽  
Primary Element

The sewerage system is a primary element of a city and is responsible for the congestion of both rain and gray water from homes and industries. It is essential to have a monitoring system and a plan to perform prior expansion in the sewerage management system, to avoid massive disruption. However, there is no monitoring system in several overpopulated cities in the world, and the expansion process faces myriad difficulties and takes much time. This paper presents a model for an intelligent sewerage management system that provides real-time monitoring without any major changes to the previous system, using water sensors, a Global System for Mobile Communications (GSM) module, and a micro-controller. The condition of the sewerage acts as an input through the sensors; then, the microcontroller stores the value in the cloud and performs waste collection depending on the current situation. Meanwhile, after processing, the information reaches the monitoring system. Various trial installations of the proposed system have shown that it enables real-time monitoring to observe live conditions and helps to prevent sewerage blockage caused by solid waste. Considering a deficient cost model, this system can intensify the performance of poorly managed sewerage systems.

The Design of Data Acquisition Storage and Real-Time Monitoring System Based on FPGA

2011 ◽  
Vol 341-342 ◽  
pp. 803-806
Author(s):  
Su Hua Liu ◽  
San Min Shen ◽  
Yong Ye ◽  
Ji Jun Xiong
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Digital Signal ◽  
Test System ◽  
Real Time Monitoring ◽  
Collection System ◽  
The Real ◽  
Overall Design ◽  
The Stability ◽  
And Storage

In the test system, all kinds of signals need to be processed. In order to meet the need of test system,we propose a kind of method of overall design of the real-time monitoring and storage of analog signal and digital signal. And we descript that how the data is sent to PC to real-time monitor and how we read out the data of the storage, and at the same time, the effect of the real-time monitoring is mentioned. After the application of the practice, the stability and the reliability of the collection system get confirmed.

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