## 3 Results
### Analysis of AI and Smart Technology Applications Across Industry Sectors
#### 3.2.5 Integration of AI and Smart Technologies in Safety Management for the Energy and Power Sector  
In the energy and power sector, key safety management factors such as gas safety and risk management, power grid and energy management, real-time monitoring and alert systems, urban gas facility risk management, and resource consumption and energy efficiency management are significantly enhanced through the integration of Artificial Intelligence (AI) and smart technologies. AI-driven solutions include the development of intelligent gas meters and automated fire suppression systems, effectively managing gas-related risks. Wireless modularization and networking technologies enable robust real-time monitoring and alert systems, ensuring immediate responses to hazards. Additionally, web-based safety management systems support data-driven decision-making by integrating comprehensive safety data for analysis. Smart meters are crucial for power grid management, automatically controlling power supply based on appliance priority, detecting faulty cabling, and identifying recalled appliances to ensure safety. Resource consumption and energy efficiency are optimized through low-cost appliance control solutions using advanced power distribution systems. Urban gas facility risk management is enhanced by Smart Home Gas Safety Management Systems (S-GMSs), which are validated through scenario-based assessments and system tests. AI governance frameworks ensure responsible AI use in smart cities, protecting public safety while complying with regulations. Data mining and Big Data Analysis (BD Analysis) identify fire hotspots and simulate scenarios to optimize firefighting and evacuation strategies. Digital twin models provide real-time safety scenario simulations, offering immersive fire monitoring and enhancing overall safety management. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Safety Management Factor** & **AI and Smart Technology Research Methods** & **Research Number** \\ \hline Traffic Accident Prevention and Collision Avoidance & - AI-based predictive models and machine learning algorithms for real-time traffic analysis and collision avoidance. & \\ Traffic Accident Prevention and Collision Avoidance & - Utilized CNNs, ARIMA, and LSTM for traffic flow prediction and congestion warnings. & [53; 55; 58] \\  & - Implemented Steering Control Collision Avoidance Systems (SCCASs). & \\ \hline  & - Designed PIPSC/CMF framework integrating indoor GIS with Bluetooth and RFID positioning. & \\ Railway Safety and Worker Protection & - Analyzed railway accident data through literature reviews and statistics. & \\  & - Developed and evaluated safety management systems using smartphone GPS and case studies like Lac-Mégantic. & [52; 54] \\  & - Implemented OSGi-based monitoring, facial recognition, WMN, and integrated sensors. & \\  & - Created intelligent bridge management and AI-based control systems. & \\ \hline Maritime and Industrial Site Safety Management & - Developed AI-driven navigation and autonomous vessels to prevent maritime collisions. & \\  & - Employed predictive analytics for monitoring hazardous conditions. & [57; 59] \\  & - Implemented AI-powered fire detection and digital twin models for real-time safety assessments. & \\ \hline Public Transport Safety Management & - Enhanced surveillance with AI-based facial recognition and behavioral analysis. & \\  & - Utilized Big Data analytics to optimize safety protocols and emergency responses. & \\  & - Developed AI-powered predictive models for public transport safety. & [56] \\  & - Implemented AI-based real-time monitoring systems. & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: AI and smart technology research methods for safety management factors in the transport and logistics sector. These applications demonstrate how AI and smart technologies address critical safety challenges in the energy and power sector, leading to improved operational efficiency, enhanced safety outcomes, and sustainable energy management.