## 3 Results
### Analysis of AI and Smart Technology Applications Across Industry Sectors
#### 3.2.1 Integration of AI and Smart Technologies in Safety Management for the Construction Sector
Additionally, literature reviews and accident statistics analyses identify common accident types among railway workers, informing the design of safety management systems that utilize smartphone GPS technologies. The effectiveness of Safety Management Systems (SMSs) is further evaluated through case studies, such as the Lac-Megantic accident, and comparative analyses of regulatory models. In maritime safety, AI-driven navigation systems and autonomous vessels utilize AI to prevent collisions at sea. Predictive analytics support industrial site safety by automating the monitoring of hazardous conditions. Public transport safety management is enhanced by AI-enhanced surveillance systems employing facial recognition and behavioral analysis to detect suspicious activities. Furthermore, Big Data analytics optimize safety protocols and emergency responses, ensuring timely and effective measures in public transportation environments. These applications demonstrate how AI and smart technologies address critical safety challenges in the transport and logistics sector, leading to improved operational efficiency \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
**Urbanization and Public Safety Management** & - Designed the PIPSC/CMF framework integrating indoor GIS with Bluetooth and RFID-based positioning technologies. - Implemented smart street lighting systems with GSM, GPS, cameras, LED lighting, and emergency buttons using Arduino and ATMEGA 32 microprocessors. - Conducted crime statistics analysis and case studies to optimize urban safety measures. & [47; 49; 51] \\ \hline
**Disaster and Fire Safety Management** & - Developed AI-powered disaster response platforms integrating historical data, intelligent CCTV, sensors, satellite information, and social network data. - Utilized data mining and BD Analysis to identify fire hotspots and simulate fire scenarios. - Implemented AIOT-based fire detection systems within digital twin frameworks for real-time safety assessments. & [47; 49; 51] \\ \hline
**Hazardous Workplaces and Industrial Safety** & - Employed AI algorithms for monitoring hazardous conditions and predicting potential workplace hazards. - Integrated safety tags with accelerometer sensors and developed command unit terminals for real-time hazard communication. - Built centralized control servers to manage safety data across multiple organizations. & [42; 43; 50] \\ \hline
**Integration of Smart Technologies and Public Safety** & - Utilized IoT sensors and AI governance frameworks to enhance public safety in smart cities. - Developed smart mobile applications for real-time safety notices, checklist creation, and daily safety activity management. - Implemented AI-based monitoring systems for immersive fire monitoring and emergency response. & [42; 43; 50] \\ \hline \hline \end{tabular}
\end{table} 
Table 4: AI and smart technology research methods for safety management factors in the disaster and public safety sector. and enhanced safety outcomes. Table 5 presents AI and smart technology research methods for safety management factors in the transport and logistics sector.