Reasoning Support for Risk Prediction and Prevention in Independent Living 3

![0_image_0.png](0_image_0.png)

![0_image_1.png](0_image_1.png)

- A Wireless Sensor Network (WSN), composed of infrastructural nodes equipped with several sensors and a wearable monitoring device, used for gathering data about the user and the environment.

- A reasoning component that makes it possible to analyse the health evolution of patients in order to identify and predict what is best for the patient in his specific context (Tonelli 2001).

Figure 1 shows a high-level overview of the architecture of our system and the correlation between its components.

Wireless Sensor Networks (WSNs) (Akyildiz et al. 2002) consist of nodes that are capable of interacting with the environment by sensing and controlling physical parameters; the nodes use packet radio communication to exchange data. These networks are typically used to collect data for long periods of time without assistance.

Specific scenarios for WSNs include habitat monitoring, industrial control, embedded sensing, medical data collection, building automation, fire detection, traffic monitoring, etc.

For the SINDI Wireless Sensor Network (SINDI-WSN) we designed, implemented and prototyped new WSN devices specifically conceived for people monitoring and tracking. These devices use a commercial wireless microcontroller (Jennic JN5139)
with IEEE 802.15.4 radio and are equipped with heterogeneous sensors.

The SINDI-WSN is composed of:
- A Master Processor, the coordinator node of the network. It is the gateway of the network and it has storage, processing power and main memory capabilities in the ballpark of an average PC.

- Reference Nodes. They are always active and connected to household power, used for network coordination but also with sensing capabilities. The presence of an always active base node in every zone simplifies data routing because the data-gathering nodes are guaranteed to always find a listening node. Therefore, they can simply send a message with the proper sensor data and quickly enter in sleep-mode without wasting precious energy.