Abstract
The disclosure describes techniques to automatically determine the presence of an emergency situation such as a natural disaster (e.g., an earthquake, cycle, or other event) or man-made crisis (e.g., an accident or other event) using machine learning and artificial intelligence techniques. When an emergency situation is determined to be present in a location, users of a social media platform or other online service within a crisis radius of the location are identified based on geolocation data from user devices. The users are provided with an alert regarding the emergency situation and a SOS button or other mechanism that can be used to generate a distress signal. Location information and user profile information of the identified users is transmitted to a third party such as emergency response services in response to the SOS button being triggered by the user. The user is directly connected with the third party via text, audio, or video chat, enabling rescue teams and emergency services to communicate with the user. The described techniques leverage the widespread availability of portable user devices and the record of users available to an online service such as a social media platform to quickly alert users to an emergency situation, enable them to generate a distress signal, and to connect them to emergency responders. The techniques also guide emergency responders to locations where users are in distress and can help reduce their response time.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Anonymous, "Assisting Users in an Emergency Situation Using Geolocation Data and SOS Button", Technical Disclosure Commons, (June 07, 2023)
https://www.tdcommons.org/dpubs_series/5946