An IoT Based Smart Garbage Monitoring and Disposal Support System

Vamsi, T. M. N.; Chakravarthi, G. Kalyan; Lanka, Pratibha; Divakar, B.

doi:10.1109/iccmc51019.2021.9418289

Cited by 14 publications

(6 citation statements)

References 4 publications

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“…In contrast to [3], [4], [6], [9], [11] not yet using LoRa, still using wifi, only [5] already using LoRa, without any waste sorting device, not discussing the placement of the waste bin. In fact, with the various parameters required, it is very important to consider the placement of waste to optimize collecting and disposing of waste.…”

Section: Development Clustering Methods For Placement…mentioning

confidence: 99%

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LoRa-Based Smart Waste Bins Placement using Clustering Method in Rural Areas of Indonesia

Abidin1¹

2022

ijasca

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ATP Tennis stands for the “The Association of Tennis Professionals” which is the primary governing body for male tennis players. ATP was formed in Sep 1972 for professional tennis players. A study has been done on tennis players’ datasets to implement supervised machine learning techniques to illustrate match data and make predictions. An appropriate dataset has been chosen, data cleaning has been implemented to extract anomalies, data is visualized via plotting methods in R language and supervised machine learning models applied. The main models applied are linear regression and decision tree. Results and predictions have been extracted from the applied models. In the linear regression model, the correlation is calculated to find the relation between dependent and independent variables, furthermore the results and prediction are extracted from the linear regression model. Also, three hypotheses are applied for multiple linear regression model. The decision tree modeled the best of 3 or best of 5 sets of matches and predicted which set of matches would be considered best. Keywords: Machine Learning, supervised learning, linear regression, decision tree, R language, Tennis, ATP.

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Section: Development Clustering Methods For Placement…mentioning

confidence: 99%

“…IoT-based systems are used to help manage waste disposal [3] and to educate resident's rural areas [4], the waste collection by optimizing the shortest path [5], [6], to control waste water treatment [7], [8]. Smart waste bin design and can interact human interaction via remote computer is realized through the mobile terminal [9].…”

Section: Introductionmentioning

confidence: 99%

LoRa-Based Smart Waste Bins Placement using Clustering Method in Rural Areas of Indonesia

Abidin1¹

2022

ijasca

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“…Since it might be difficult for consumers to describe their degree of happiness or discontent with the cloud service providers with regard to the qualities, there is generally confusion in the sharp data. [4]. The approach was used in actual hackers, especially the widespread assaults on Latvia and the Islamic Republic, and the outcomes of the evaluation of the online assaults were given.…”

Section: International Journal On Recent and Innovation Trends In Com...mentioning

confidence: 99%

“…We have seen tremendous environmental changes over the last 17 years, including population growth and technological development. These adjustments show the necessity for efficient waste .management practices to ensure clean surroundings and minimize health hazards [4].Garbage containers that are regularly overflowing have a number of negative effects. The emergence of a repulsive and filthy odour in the neighbourhood is one important impact.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Garbage Management Based on IoT

Naveen Raja S.M

2023

IJRITCC

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Smart Waste Monitoring: To track the amount of waste in bins and containers, IOT-enabled garbage management systems use sensors and connected devices. These sensors can communicate real-time data to a centralized monitoring system and can identify the fill level. This data aids in streamlining waste collection routes, cutting back on pointless pickups, and enhancing garbage management effectiveness as a whole. Effective Resource Allocation: By giving precise data on waste generation patterns and trends, IOT-based garbage management systems enable optimal resource allocation. This information can be used by municipal authorities to make well-informed decisions on waste collection schedules, resource deployment, and staffing levels. IOT-based waste management solutions have the potential to make trash management procedures more effective and efficient while also being more affordable. The best garbage collection routes, operational cost reductions, and resource utilization may all be achieved with the aid of research into the best deployment strategies for IOT sensors and devices. Environmental Impact and Sustainability: Research Objective: Clearly identify the research objective, for example, by assessing how well IOT-based garbage management systems gather waste and allocate resources. Data gathering: Compile pertinent information on the methods used for trash generation, collection, and resource use. On-site observations, employee interviews, and database access for waste management operations are all effective ways to accomplish this. Gather information on IOT sensor technologies and their capabilities as well. Taken As alternative for Smart Waste Bins, Waste Level, Sensors, AI Recycling, Robots, E-Waste Kiosks. Taken for Evaluation preference is Reliability, Mobility, Service Continuity, User Convenience., and Energy Efficiency. Smart Waste Bins has performed more when compare to with other Real-Time Monitoring: The Internet of Things (IOT) can be used in waste management to enable real-time monitoring of trash cans or bins can be used to enhance garbage sorting procedures. Smart bins with cameras and sensors can automatically recognize and sort various types of rubbish. These smart bins can identify and categorise rubbish by utilizing IOT technology. on their material composition or recycling category.

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“…In their research, they concluded that the usage of smart dustbins on the campuses creates interest among the students to throw the garbage in the bins only. Vamsi et al (2021) developed an IoTbased application called "Smart garbage monitoring and disposable support system". This application gives the real-time status of each trash bin.…”

Section: Related Workmentioning

confidence: 99%

Quantifying Reliability Indices of Garbage Data Collection IOT-based Sensor Systems using Markov Birth-death Process

Kumar,

Kumar

2023

Int. j. math. eng. manag. sci.

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The aim of this paper is to analyze the performance of a Garbage data collecting sensor network system (GDCSNS) through mathematical modelling and a reliability approach. The reliability assessment of such a system is essential to ensuring that it can collect data related to garbage at different locations consistently and accurately. After the determination of the reliability measures of the system, the next aim is to identify the weakest sensors of the system so that a timely maintenance strategy for the weakest sensor can be planned to avoid disruption in the collection of data from the sensor systems. In the considered system, three sensors have been installed at various location in the city that send the information to the center office (hub point) and then from the center office to the person who is responsible for collecting the garbage from the location and dumping it at some predefined places. These sensors collect data related to garbage level, weight, and other information and send it to computers at the city's central office. Markov modelling has been used to model the system. Based on the mathematical model, a state transition diagram and a set of Kolmogorov time-dependent differential equations have been obtained. The various state probabilities (explicit expressions) related to the performance of the system, namely, Reliability, Mean time to failure, have been obtained to understand the different maintenance policies that can be used. A sensitivity analysis has also been performed to determine the weakest sensor among the sensors.

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An IoT Based Smart Garbage Monitoring and Disposal Support System

Cited by 14 publications

References 4 publications

LoRa-Based Smart Waste Bins Placement using Clustering Method in Rural Areas of Indonesia

LoRa-Based Smart Waste Bins Placement using Clustering Method in Rural Areas of Indonesia

Evaluation of Garbage Management Based on IoT

Quantifying Reliability Indices of Garbage Data Collection IOT-based Sensor Systems using Markov Birth-death Process

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