Juan Brignardello Vela
Juan Brignardello, asesor de seguros, se especializa en brindar asesoramiento y gestión comercial en el ámbito de seguros y reclamaciones por siniestros para destacadas empresas en el mercado peruano e internacional.
The Tokyo Metropolitan Government has taken the lead in implementing advanced technology to improve response to natural disasters by launching a new artificial intelligence system designed to detect and assess the consequences of catastrophes such as earthquakes in real-time. This system is being developed in a context of growing concern about seismic activity in the region, especially following a magnitude 5+ earthquake that shook the city in October 2021. The earthquake in question not only highlighted Tokyo's vulnerability to natural disasters but also occurred during a period marked by severe weather conditions, including torrential rains. These events led the local government to recognize the need for a more effective method of responding to emergency situations. The creation of this AI system is a direct response to that need, aiming to minimize reaction time and maximize the effectiveness of rescue operations. The new system uses strategically placed high-resolution cameras throughout the Japanese capital and is capable of quickly identifying fires, landslides, and other hazards associated with disasters. This instant detection capability is crucial in chaotic situations, where every second counts. By providing real-time information to relevant authorities, such as the police and emergency services, it is expected that rescue operations will be more coordinated and efficient. Since its development in 2022, the system has undergone testing and began large-scale operations in March 2023. With the recent warning from the Japan Meteorological Agency (JMA) about the risk of a 'megathrust earthquake' in the Nankai Trough, the implementation of this technology becomes even more relevant. The JMA estimates a 70% probability that a major earthquake will affect Tokyo in the next 30 years, making the government's efforts vital to prepare the population and mitigate potential losses. In addition to detection through cameras, the AI system also incorporates social media analysis to complement the information gathered. This approach allows the government to have a broader and up-to-date view of the conditions in the affected areas, which can be immensely helpful in decision-making and resource allocation. Support tools for damage certification in homes are also an important addition, facilitating local governments in issuing certificates to disaster victims. The damage assessment conducted by the metropolitan government in 2022 projects that a 'megathrust earthquake' in the Nankai Trough could generate a tsunami with waves reaching between 2 and 2.6 meters in Tokyo Bay. This not only underscores the need for a rapid response system but also serves as a reminder of the fragility of infrastructure in a densely populated and highly urbanized city. The data obtained from this new system could be crucial in saving lives. According to projections, a strong earthquake in southern Tokyo could tragically result in the loss of approximately 6,100 lives and damage around 194,000 buildings. In light of these alarming statistics, it is imperative that authorities have effective tools to manage the crisis from the very first moment. The Tokyo Metropolitan Government's commitment to innovation and technology in disaster management is a positive step towards urban resilience. The implementation of this AI system not only provides a faster and more efficient response to emergencies but may also serve as a model for other disaster-prone cities around the world. As the world faces climate change and increasing extreme natural phenomena, Tokyo demonstrates that the use of advanced technology can be an indispensable ally in protecting its citizens. As the system continues to evolve and improve, its impact on the safety and well-being of the population is expected to be significant, setting a new standard in disaster management.