Smart Patrolling Based on Spatial-Temporal Information Using Machine Learning

The COVID-19 pandemic highlighted the urgent need for effective surface disinfection solutions, which has led to the use of mobile robots equipped with ultraviolet (UVC) lamps as a promising technology. This study aims to optimize the navigation of differential mobile robots equipped with UVC lamps to ensure maximum efficiency in disinfecting complex environments. Bio-inspired metaheuristic algorithms such as the gazelle optimization algorithm, whale optimization algorithm, bat optimization algorithm, and particle swarm optimization are applied. These algorithms mimic behaviors of biological beings such as the evasive maneuvers of gazelles, the spiral hunting patterns of whales, the echolocation of bats, and the collective behavior of flocks of birds or schools of fish to optimize the robot’s trajectory. The optimization process adjusts the robot’s coordinates and the time it takes to stops at key points to ensure complete disinfection coverage and minimize the risk of excessive UVC exposure. Experimental results show that the proposed algorithms effectively adapt the robot’s trajectory to various environments, avoiding obstacles and providing sufficient UVC radiation exposure to deactivate target microorganisms. This approach demonstrates the flexibility and robustness of these solutions, with potential applications extending beyond COVID-19 to other pathogens such as influenza or bacterial contaminants, by tuning the algorithm parameters. The results highlight the potential of bio-inspired metaheuristic algorithms to improve automatic disinfection and achieve safer and healthier environments.

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Integrating Generative AI and IoT for Sustainable Smart Tourism Destinations

Suanpang,

Pothipassa

2024

Sustainability

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This paper aims to develop a groundbreaking approach to fostering inclusive smart tourism destinations by integrating generative artificial intelligence (Gen AI) with natural language processing (NLP) and the Internet of Things (IoT) into an intelligent platform that supports tourism decision making and travel planning in smart tourism destinations. The acquisition of this new technology was conducted using Agile methodology through requirements analysis, system architecture analysis and design, implementation, and user evaluation. The results revealed that the synergistic combination of these technologies was organized into three tiers. The system provides information, including place names, images, descriptive text, and an audio option for users to listen to the information, supporting tourists with disabilities. Employing advanced AI algorithms alongside NLP, developed systems capable of generating predictive analytics, personalized recommendations, and conducting real-time, multilingual communication with tourists. This system was implemented and evaluated in Suphan Buri and Ayutthaya, UNESCO World Heritage sites in Thailand, with 416 users participating. The results showed that system satisfaction was influenced by (1) the tourism experience, (2) tourism planning and during-trip factors (attention, interest, and usage), and (3) emotion. The relative Chi-square (χ2/df) of 1.154 indicated that the model was suitable. The Comparative Fit Index (CFI) was 0.990, the Goodness-of-Fit Index (GFI) was 0.965, and the model based on the research hypothesis was consistent with the empirical data. This paper contributions significant advancements in the field of smart tourism by demonstrating the integration of Gen AI, NLP, and the IoT and offering practical solutions and theoretical insights that enhance accessibility, personalization, and environmental sustainability in tourism.

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Smart Patrolling Based on Spatial-Temporal Information Using Machine Learning

Cited by 3 publications

References 43 publications

Navigating the Dark: Advances in Robotic Night Patrol with D-Block Mask Electric EEL Dense Nested R-CNN for Enhanced Safety

Navigating the Dark: Advances in Robotic Night Patrol with D-Block Mask Electric EEL Dense Nested R-CNN for Enhanced Safety

Route Optimization for UVC Disinfection Robot Using Bio-Inspired Metaheuristic Techniques

Integrating Generative AI and IoT for Sustainable Smart Tourism Destinations

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