One distinctive feature of ambient assisted living-oriented systems is the ability to provide assistive services in smart environments as elderly people need in their daily life. Since Time-Of-Flight vision technologies are increasingly investigated as monitoring solution able to outperform traditional approaches, in this work a monitoring framework based on a Time-Of-Flight sensor network has been investigated with the aim to provide a wide-range solution suitable in several assisted living scenarios. Detector nodes are managed by a low-power embedded PC to process Time-Of-Flight streams and extract features related with person’s activities. The feature level of detail is tuned in an application-driven manner in order to optimize both bandwidth and computational resources. The event detection capabilities were validated by using data collected in real-home environments.