LoRaWAN for tracking inland routes of plastic waste: Introducing the smart TRACKPLAST bottle

Ponis, Stavros T.; Plakas, George; Aretoulaki, Eleni; Tzanetou, Dimitra; Maroutas, Theodoros Nikolaos

doi:10.1016/j.clwas.2022.100068

Cited by 4 publications

(1 citation statement)

References 13 publications

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“…Furthermore, artificial intelligence can optimize the recycling process by analyzing the data from the recycling process and suggesting improvements (Pouyanfar et al 2022 ). Additionally, artificial intelligence can be essential in measuring and tracking waste (Ponis et al 2023 ). This can help to ensure that materials are recycled most efficiently and effectively.…”

Section: Artificial Intelligence In Waste Managementmentioning

confidence: 99%

Artificial intelligence for waste management in smart cities: a review

Fang

Chen

et al. 2023

Environ Chem Lett

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The rising amount of waste generated worldwide is inducing issues of pollution, waste management, and recycling, calling for new strategies to improve the waste ecosystem, such as the use of artificial intelligence. Here, we review the application of artificial intelligence in waste-to-energy, smart bins, waste-sorting robots, waste generation models, waste monitoring and tracking, plastic pyrolysis, distinguishing fossil and modern materials, logistics, disposal, illegal dumping, resource recovery, smart cities, process efficiency, cost savings, and improving public health. Using artificial intelligence in waste logistics can reduce transportation distance by up to 36.8%, cost savings by up to 13.35%, and time savings by up to 28.22%. Artificial intelligence allows for identifying and sorting waste with an accuracy ranging from 72.8 to 99.95%. Artificial intelligence combined with chemical analysis improves waste pyrolysis, carbon emission estimation, and energy conversion. We also explain how efficiency can be increased and costs can be reduced by artificial intelligence in waste management systems for smart cities.

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Section: Artificial Intelligence In Waste Managementmentioning

confidence: 99%

Artificial intelligence for waste management in smart cities: a review

Fang

Chen

et al. 2023

Environ Chem Lett

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SiSMA‐SWMS: Signature‐based Secure Monitoring Approach for Smart Waste Monitoring Systems

Lama,

Karmakar

2024

Security and Privacy

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With the speedy growth of the populace, corresponding waste also grows, notably raising greater concern about the monitoring of waste in urban areas. Although the traditional method of waste monitoring has benefited city waste management systems, it remains time‐consuming, inefficient, and detrimental to public health. This situation can be improved by integrating advanced technologies, which can significantly enhance the flexibility and performance of waste monitoring systems. However, these advanced technologies encounter numerous security challenges. In this article, we have implemented a signature‐based monitoring approach to oversee the status of smart bins. To ensure the security, robustness, and reliability of the introduced protocol, we utilized tools such as AVISPA, Scyther, the ROR model, and Mao and Boyd logic. As discussed in the informal security analysis, the introduced protocol successfully fulfills the security requirements for smart waste monitoring systems. Finally, an in‐depth comparative analysis of the related works and the introduced protocol shows that the latter provides greater security, reliability, and efficiency. As a result, the reliability and hardness of the cryptographic operations used in the introduced protocol make it secure enough to use in real‐world applications.

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Review on environmental aspects in smart city concept: Water, waste, air pollution and transportation smart applications using IoT techniques

Salman

Hasar

2023

Sustainable Cities and Society

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LoRaWAN for tracking inland routes of plastic waste: Introducing the smart TRACKPLAST bottle

Cited by 4 publications

References 13 publications

Artificial intelligence for waste management in smart cities: a review

Artificial intelligence for waste management in smart cities: a review

SiSMA‐SWMS: Signature‐based Secure Monitoring Approach for Smart Waste Monitoring Systems

Review on environmental aspects in smart city concept: Water, waste, air pollution and transportation smart applications using IoT techniques

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