This report presents DropWarnify, an integrated system designed for monitoring and alerting fall events, especially among older adults. The project combines a mobile application with sensors embedded in wearable devices capable of identifying abrupt motion patterns, falls, and significant changes in user behavior. When a critical event is detected, the system sends immediate alerts accompanied by contextual and location information, enabling family members or caregivers to respond quickly in emergency situations. The solution relies on a distributed architecture based on Mobile Hub and ContextNet, technologies that enable the structured transmission of sensor events and the real-time processing of continuous data streams. The Mobile Hub acts as an intermediate layer on the device, collecting, organizing, and transmitting information generated by sensor and geolocation modules. These data are forwarded to ContextNet, an event-oriented platform responsible for interpreting and distributing information to other system components, ensuring robustness, scalability, and reliability in the monitoring workflow. The development of the application was guided by an analysis of existing solutions and interviews with older adults to better understand real needs related to usability, accessibility, and safety. The implementation was carried out using the Dart programming language and the Flutter framework, chosen for their performance, sensor integration capabilities, and compatibility with Wear OS devices. The result is an assistive technological solution aimed at improving the autonomy, safety, and quality of life of its users.