Smart Solid Waste Management System Using Blockchain and IoT for Smart Cities

Paturi, Mohinish; Puvvada, Sampath; Ponnuru, Badhari Sai; Simhadri, Mounika; Egala, Bhaskara S.; Pradhan, Ashok Kumar

doi:10.1109/ises52644.2021.00107

Cited by 17 publications

(7 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Select the best site for bin installation based on real-time space and population density in the area [22] Integration of IoT and machine learning algorithm (linear regression) Predict the fill-up time of a particular bin [18] Integration of IoT and (RFID) radio frequency identification Increase utilization of bin by rewarding points based on weight [23] Integration of IoT and blockchain [24] IoT and tensor flow Waste classification into biodegradable and non-biodegradable waste [25] Faster region CNN [27] Identification of e-waste and its subsequent categorization [28] Recognition of street litter and categorization [29] Detection of garbage for street cleanliness evaluation [30] Separation of biodegradable and non-biodegradable waste [31] YOLOv2 and YOLOv3 CNN Classification of garbage container after detection [32] YOLOv3 and YOLOv3 Tiny-CNN Segregation of waste for recycling and reuse or for disposal 6…”

Section: Referencesmentioning

confidence: 99%

See 1 more Smart Citation

GRUBin: Time-Series Forecasting-Based Efficient Garbage Monitoring and Management System for Smart Cities

Mishra

Vajire

Saxena

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

The waste management of an evolving smart city environment is one of the most important tasks as the living conditions and health of the population depend on proper waste management. Currently deployed systems are failing to monitor the garbage production as they use IoT-based pipelines to monitor the production in a locality, but often the device is used to get destroyed by the frequent use of dustbin. This leads to an increase in expenditure and affects the sustainability of the system. In this work, we propose an efficient and scalable garbage monitoring and collection methodology based on time-series forecasting techniques. The proposed system is also cost-effective because of the iterative deployment of rented IoT sensors, which are used to collect time series format data and then used to train the forecasting module to learn the temporal representation of the data that can produce accurate results for monitoring the fill-up time of the garbage collector. We also propose an efficient collection in-routing technique based on the ranking of bin stations on the basis of temporal and spatial data of the fill-up time and route location to minimize the collection time by making an efficient routing algorithm for garbage collection. This concept of garbage collection will be very useful for smart city planners.

show abstract

Section: Referencesmentioning

confidence: 99%

“…is would make the process more efficient and save unnecessary travel of garbage collecting vehicles, which will reduce air pollution and fuel consumption. Reference [23] in their paper discussed a unique smart waste management system that is based on technologies such as blockchain and the Internet of things in smart bins.…”

Section: Introductionmentioning

confidence: 99%

GRUBin: Time-Series Forecasting-Based Efficient Garbage Monitoring and Management System for Smart Cities

Mishra

Vajire

Saxena

et al. 2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

show abstract

“…Such aspect ensures confidentiality and privacy. Due to the inherent merits of Blockchain, Healthcare, [14][15][16] Banking, [17][18][19] Supply Chain Management, [20][21][22] and the Internet of Things [23][24][25] are relying on it to enhance the security aspects. Spending threat.…”

Section: Features Of Cyber Security Descriptionmentioning

confidence: 99%

An anomaly detection on blockchain infrastructure using artificial intelligence techniques: Challenges and future directions – A review

Chithanuru

Ramaiah

2023

Concurrency and Computation

View full text Add to dashboard Cite

SummaryRecently, Blockchain cryptographic distributed transaction ledger technology finds its usage in many applications. The application's ledgers implemented through Blockchain, ensures tamper‐proof transactions, and in turn the applications became robust enough against cyber‐attack But still adversaries put forward their efforts in detecting the vulnerabilities in the infrastructure to execute their ill intent. In the literature, many counter measures techniques are presented to address the security breaches on the Blockchain. Detecting as well mitigating from the possible anomalies against on blockchain infrastructure through AI techniques is the greatest attempt of this article, and which is much needed now. Hence, this review article enlightens the readers with the essence of cyber security, the security aspects of Blockchain, its infrastructure vulnerabilities, various Blockchain‐enabled use cases along with the their challenges. Primarily, anomaly detection on Blockchain infrastructure through Artificial Intelligence Techniques is focused. A detailed analysis of Artificial Intelligence Techniques in detecting the anomalies with the help of Blockchain and also how these two technologies complement each other was demonstrated with the help of suitable use cases. The merits, challenges along with the possible future directions, while integrating Blockchain with Artificial Intelligence Techniques are presented for the benefit of research community.

show abstract

“…Numerous studies have explored the integration of technologies to optimise waste collection, sorting, and recycling processes. For instance, IoT sensors have been used to collect data on waste generation, predict waste amounts, and optimise waste bin collection processes, as demonstrated in [9,10]. In [9], the authors designed a system that uses IoT sensors to collect data on waste generation and designed an algorithm to predict the amount of waste generated.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, IoT sensors have been used to collect data on waste generation, predict waste amounts, and optimise waste bin collection processes, as demonstrated in [9,10]. In [9], the authors designed a system that uses IoT sensors to collect data on waste generation and designed an algorithm to predict the amount of waste generated. The system also provided information on the location and capacity of waste bins to optimise the collection process.…”

Section: Introductionmentioning

confidence: 99%

Improving the Trustworthiness of Traceability Data in Food Supply Chain Using Blockchain and Trust Model

Leteane,

Ayalew

2024

The JBBA

View full text Add to dashboard Cite

The current state of recycling systems is marked by significant impediments to their efficacy. A lack of transparency often pervades these systems, which may result in an increased likelihood of fraudulent and corrupt activity. Additionally, traceability pertaining to recycled materials frequently proves inadequate. Together, these inefficiencies in the collection and processing of recyclables can lead to higher costs and environmental impact. Furthermore, low incentives may deter individuals and businesses from participating in recycling initiatives. Certain recycling systems may also suffer from limited compatibility with specific materials, further reducing their effectiveness. To address these challenges, we propose a permissioned Ethereum blockchain-based system that aims to incentivise and encourage recycling practices in a transparent and secure manner. The platform's modular and multi-layered design makes it adaptable to various recycling scenarios, allowing it to handle diverse types of recyclable materials. Automated and streamlined recycling processes are achieved through the use of smart contracts. The proposed system offers a secure, transparent, and efficient platform for the management of recycling processes, promoting environmentally responsible behaviour towards a circular economy. Potential applications for the system include waste disposal and recycling management for smart cities, waste management for organisations, and tracking and management of operations for recycling companies. The platform is highly versatile and can accommodate various use cases in the recycling industry, including those involving traceable and untraceable materials, as well as individual and corporate use cases.

show abstract

Smart Solid Waste Management System Using Blockchain and IoT for Smart Cities

Cited by 17 publications

References 5 publications

GRUBin: Time-Series Forecasting-Based Efficient Garbage Monitoring and Management System for Smart Cities

GRUBin: Time-Series Forecasting-Based Efficient Garbage Monitoring and Management System for Smart Cities

An anomaly detection on blockchain infrastructure using artificial intelligence techniques: Challenges and future directions – A review

Improving the Trustworthiness of Traceability Data in Food Supply Chain Using Blockchain and Trust Model

Contact Info

Product

Resources

About