In environmental sensors are connected objects capable of providing various types of information like location, position, the individual’s movements, and contextual elements which can be compared to data collected via sensor embedded on or implanted in the individual and including the validation of alarm, like in the case of falls. They pose particular ethical problems as they are types of surveillance that can affect the individual’s private life, even their privacy, depending on where they are placed. This point is particularly sensitive in the case of video capture. So this kind of sensor can also be associated with the robotic device with which they interact to allow them to adapt to the context or the need of the person with whom they are meant to interact. The monitoring of the individual and their health is not the first objective for some sensors as air quality sensors, light sensors, smoke detectors, etc. exist.However, data they collected can be cross-reference with data from other sources which contribute to the production of potentially Personalize health information and eventually the generation of an alarm.
- Environmental sensors are now evolved and there are now many applications o9f WSNs to earth science research. This includes sensing volcanoes, oceans, glaciers, forests, etc. some other major areas such as air pollution monitoring, forest fire detection, landslide detection, etc.
Air Pollution Monitoring
- WSNs have been deployed in several cities to monitoring the concentration of dangerous gases. These can take advantage of ad hoc wireless links, making them more mobile for testing reading in different areas.
Forest Fire Detection
- A network of sensor nodes that is installed in a forest to detect fires. The node can be equipped with sensors to measure temperature, humidity, and gases produ8ced by fires in the trees or vegetation. Early detection is very crucial and WSNs, the firefighters know when afire starts, how and where it is spreading.
- A landslide detection system makes of a WSN to detect the slight movements of soil and changes in various parameters that may occur before or during a landslide. Also with the data, it may be possible to predict the occurrence of a landslide long before it happens.