Marine debris awareness improvement using immersive virtual reality

Article Green & Sustainable Science & Technology

In-Stream Marine Litter Collection Device Location Determination Using Bayesian Network

Abdullah Battawi et al.

Summary: Increased waste generation, plastic production, and poor environmental stewardship have led to a rise in floating litter. Efforts have been made to mitigate this issue, with various methods for removing floating litter depending on the location. This study utilized Bayesian Network technology and criteria analysis to determine the most appropriate setup location for an in-stream litter collection device. The results show the potential practicality of this approach for coastal areas.

SUSTAINABILITY (2022)

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Article Engineering, Industrial

Implementing Virtual Reality technology for safety training in the precast/prestressed concrete industry

Sayali Joshi et al.

Summary: The precast/prestressed concrete industry recognizes the hazards employees face and invests significant resources in mitigating risks. It is crucial for employees to receive appropriate safety training before starting work, and Virtual Reality (VR) offers a cost-effective and engaging alternative for safety training. The development of a VR training module aimed at reducing common plant injuries shows promising results in efficacy and effectiveness analyses compared to traditional training methods.

APPLIED ERGONOMICS (2021)

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Article Transportation Science & Technology

Floating marine debris mitigation by vessel routing modeling and optimization considering carbon emission and travel time

Gang Duan et al.

Summary: Macro-marine debris is a global issue, and this paper proposes using vessels and optimal routing network to collect it. By utilizing advanced technology and modeling software, a bi-objective model is developed to minimize travel time and carbon emission. The proposed algorithm balances efficiency, emission reduction, and vessel speed to achieve low carbon emission and cost effectiveness.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2021)

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Article Computer Science, Artificial Intelligence

Vehicle operating state anomaly detection and results virtual reality interpretation

Morteza Alizadeh et al.

Summary: The paper presents an ARIMA-based anomaly detection framework to identify abnormal states of vehicles using multiple-channel operating time-series data, and visualize the differences between normal and abnormal states through a VR tool. The proposed approach shows good performance in the validation using a large dataset of operational performance channels of a specific vehicle over 14 days.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

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Review Engineering, Industrial