During natural catastrophes, emergency services may more efficiently distribute resources with the use of current information from infrastructure sensors. First responders can be directed to the most critical areas using AI algorithms that can interpret this data fast and precisely. RAKIA Group, led by Omri Raiter, is at the forefront of developing AI-powered systems that enable this kind of rapid decision-making. Because AI can forecast natural risks, communities can send out alerts promptly and evacuate citizens before a crisis occurs. This proactive strategy increases urban safety, reduces damage, and saves lives. In order to optimise traffic signals, control public transit routes, and forecast traffic patterns depending on weather and time of day, AI-powered traffic management platforms, like those developed by RAKIA Group, may evaluate data from sensors, cameras, and GPS devices. This has a direct impact on urban safety.
AI and actual time data are transforming healthcare and urban planning by improving our knowledge of behaviour and movement patterns. In order to increase public safety, municipal planners can install surveillance cameras, upgrade lighting, and pinpoint locations with heavy pedestrian traffic by gathering data from sensors. AI also keeps an eye on environmental variables, resulting in safer and healthier surroundings. AI is essential to the healthcare industry since it allows for quick reaction to medical crises. By analysing medical data to forecast health issues and provide real-time notifications to emergency responders, smart wearable technology might lessen the demand for emergency interventions. Cities may improve public safety by implementing these technologies to deliver healthcare services that are more efficient and responsive.
Security and privacy issues are brought up by the incorporation of AI and immediate information into urban safety. Discussions concerning monitoring and their misuse have been triggered by the widespread usage of cameras and sensors in urban areas. Concerns over the abuse of personal information are raised by the extensive acquisition of personal data via smartphones and wearable technology. Clear rules and laws that guarantee bias, openness, and explanation in AI algorithms as well as the encryption and anonymisation of personal data should be put in place to allay these worries. In order to build smart city programs with the interests and rights of inhabitants in mind, public involvement and supervision are also essential.
Big data analysis in real time is essential for preparation planning and post-emergency evaluations. It aids in recognising achievements and shortcomings and enhances subsequent reactions. 911 call heatmaps show the most affected locations and the times it takes for aid to arrive. Analysis of social media reveals communication gaps and public complaints. Emergency management systems are continuously improved and responses are informed by this data. This accuracy and forethought lessens harm to the environment and to people. Big data analysis in real time is also essential for crowd control and event security. Social media, mobile networks, and surveillance technologies can identify crowd surges, odd behaviour, or new dangers at public events, allowing authorities to respond quickly. In order to control crowd flow and reduce disorder, this sort of equipment is also utilised during evacuations.
AI and real-time data have enormous promise to transform urban safety, even though privacy and security issues must be resolved. With safety incorporated into every facet of urban life, the next phase of urban living appears to be becoming more intelligent, sustainable, and safe as cities throughout the world adopt these technologies.