An Intelligent Hierarchical Cyber-Physical System for Beach Waste Management: The BIOBLU Case Study

Cicceri, Giovanni; Guastella, Dario C.; Sutera, Giuseppe; Cancelliere, Francesco; Vitti, Mario; Randazzo, Giovanni; DiStefano, Salvatore; Muscato, Giovanni

doi:10.1109/access.2023.3317689

Cited by 2 publications

(2 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The interplay between climate change, pollution, and beach health necessitates innovative solutions that fuse the best of technology and sustainability. One such solution is presented in a paper detailing the development of an intelligent hierarchical cyber-physical system (IHCPS) for beach waste management [19]. This system, termed BeWastMan, is an autonomous solution that seamlessly integrates an unmanned aerial vehicle for aerial beach surveillance and monitoring, with a data-processing ground station and a UAV dedicated to waste collection and sorting.…”

Section: Related Workmentioning

confidence: 99%

Improving the Efficiency of Modern Warehouses Using Smart Battery Placement

Baras,

Chatzisavvas,

Ziouzios

et al. 2023

Future Internet

View full text Add to dashboard Cite

In the ever-evolving landscape of warehousing, the integration of unmanned ground vehicles (UGVs) has profoundly revolutionized operational efficiency. Despite this advancement, a key determinant of UGV productivity remains its energy management and battery placement strategies. While many studies explored optimizing the pathways within warehouses and determining ideal power station locales, there remains a gap in addressing the dynamic needs of energy-efficient UGVs operating in tandem. The current literature largely focuses on static designs, often overlooking the challenges of multi-UGV scenarios. This paper introduces a novel algorithm based on affinity propagation (AP) for smart battery and charging station placement in modern warehouses. The idea of the proposed algorithm is to divide the initial area into multiple sub-areas based on their traffic, and then identify the optimal battery location within each sub-area. A salient feature of this algorithm is its adeptness at determining the most strategic battery station placements, emphasizing uninterrupted operations and minimized downtimes. Through extensive evaluations in a synthesized realistic setting, our results underscore the algorithm’s proficiency in devising enhanced solutions within feasible time constraints, paving the way for more energy-efficient and cohesive UGV-driven warehouse systems.

show abstract

Section: Related Workmentioning

confidence: 99%

Improving the Efficiency of Modern Warehouses Using Smart Battery Placement

Baras,

Chatzisavvas,

Ziouzios

et al. 2023

Future Internet

View full text Add to dashboard Cite

show abstract

“…Owing to the above issues, it is thus critical to design mechanisms for the efficient collection and disposal of waste materials [17][18][19]. Sustainable, eco-friendly, and technologyassisted strategies are needed to develop waste dumping systems.…”

Section: Introductionmentioning

confidence: 99%

Efficient IoT-Assisted Waste Collection for Urban Smart Cities

Khan,

Ali,

Alharbi

et al. 2024

Sensors

View full text Add to dashboard Cite

Waste management is one of the many major challenges faced by all urban cities around the world. With the increase in population, the current mechanisms for waste collection and disposal are under strain. The waste management problem is a global challenge that requires a collaborative effort from different stakeholders. Moreover, there is a need to develop technology-based solutions besides engaging the communities and establishing novel policies. While there are several challenges in waste management, the collection of waste using the current infrastructure is among the top challenges. Waste management suffers from issues such as a limited number of collection trucks, different types of household and industrial waste, and a low number of dumping points. The focus of this paper is on utilizing the available waste collection transportation capacity to efficiently dispose of the waste in a time-efficient manner while maximizing toxic waste disposal. A novel knapsack-based technique is proposed that fills the collection trucks with waste bins from different geographic locations by taking into account the amount of waste and toxicity in the bins using IoT sensors. Using the Knapsack technique, the collection trucks are loaded with waste bins up to their carrying capacity while maximizing their toxicity. The proposed model was implemented in MATLAB, and detailed simulation results show that the proposed technique outperforms other waste collection approaches. In particular, the amount of high-priority toxic waste collection was improved up to 47% using the proposed technique. Furthermore, the number of waste collection visits is reduced in the proposed scheme as compared to the conventional method, resulting in the recovery of the equipment cost in less than a year.

show abstract

An Intelligent Hierarchical Cyber-Physical System for Beach Waste Management: The BIOBLU Case Study

Cited by 2 publications

References 46 publications

Improving the Efficiency of Modern Warehouses Using Smart Battery Placement

Improving the Efficiency of Modern Warehouses Using Smart Battery Placement

Efficient IoT-Assisted Waste Collection for Urban Smart Cities

Contact Info

Product

Resources

About