## 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
AI-powered disaster response platforms combine historical disaster data, intelligent CCTV, sensors, satellite information, and social network data to support real-time emergency management. Smart street lighting systems, designed with GSM, GPS, cameras, LED lighting, and emergency buttons, have been prototyped using Arduino and ATMEGA 32 microprocessors to improve urban safety. AI contributes to efficiency and cost reduction by automating safety processes and providing quantitative metrics-based evaluations through Big Data Analysis (BD Analysis) and digital twin simulations. These technological advancements support a cultural shift towards proactive safety management, emphasizing teamwork and continuous improvement. By leveraging AI and smart technologies, organizations can transition from traditional reactive approaches to predictive and preventive strategies, resulting in reduced workplace accidents and improved working conditions. Table 3 presents AI and smart technology research methods for safety management factors in the industrial sector. The convergence of these technologies in safety management demonstrates a paradigm shift across various industries, showcasing the critical role of AI in enhancing industrial safety practices. \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
**Technology-centered Approach** & - Designed the PIPSC/CMF framework integrating indoor GIS with positioning and navigation technologies. & [32; 33; 36; 39; 40] \\  & - Combined Bluetooth and RFID passive labels for indoor positioning and fire detection systems. & \\  & - Implemented digital twin frameworks for tunnel fire safety management with AIoT & \\  & -based fire detection systems.- Developed smart street lighting systems using GSM, GPS, cameras, LED lighting, and emergency buttons with Arduino and ATMEGA 32 microprocessors. & \\ \hline
**Data-driven Decision-making** & - Utilized data mining and statistical analysis to analyze fire patterns and causes. & [26; 27; 30; 32; 35] \\  & - Conducted Big Data Analysis (BD Analysis) to identify fire hotspots and simulate fire scenarios. & \\  & - Employed AI algorithms for predictive maintenance and accident prevention by analyzing operational data to forecast potential equipment failures. & \\ \hline
**Smart Environments and Real-time Monitoring** & - Developed real-time AI-based disaster response platforms integrating historical data, intelligent CCTV, sensors, satellites, and social network information. & [26; 29; 34; 35] \\  & - Implemented IoT sensors for continuous monitoring and real-time data collection in smart buildings. & \\  & - Created smart street lighting systems with integrated emergency response features. & \\ \hline
**Cultural Approach and Teamwork** & - Conducted expert interviews and surveys to gather insights on safety management strategies. & [28; 39; 40] \\  & - Developed smart mobile applications supporting real-time safety notices, checklist creation, and daily safety activity management. & \\  & - Fostered teamwork through AI-driven safety protocols and communication tools. & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: AI and smart technology research methods for safety management factors in the industrial safety sector. 2.3 Integration of AI and Smart Technologies in Safety Management for Disaster and Public Safety Sector  
In the disaster and public safety sector, key safety management factors such as urbanization and public safety management, disaster and fire safety management, hazardous workplaces and industrial safety, and the integration of smart technologies with public safety are being significantly enhanced through the integration of Artificial Intelligence (AI) and smart technologies. AI-driven solutions address these critical factors by leveraging advanced frameworks, real-time monitoring systems, and predictive analytics.