# A Review of Internet of Things Technologies for Ambient Assisted Living Environments
## 5 Discussion
### The Need for Localisation, Tracking and Human Activity Detection  
Many AAL applications need information about the position or movements of a human, or even extremities or hearts. The requirements for localization, tracking and activity detection systems can be manifold. Most important is that those systems must work in indoor environments such that many solutions, e.g., based on Global Positioning System (GPS), cannot be used [146]. Accuracy can range from centimeters, e.g., if movements of extremities shall be detected, to many meters, e.g., if it shall be detected whether a person is in a room. Usability is influenced by the fact whether the user must carry an additional device. Systems based on video monitoring can yield privacy issues. Deployment and operation costs depend on the coverage of a solution, i.e., whether sensors can detect positions in ranges of few meters or tens/hundreds of meters.  
Systems providing position or movement information can be device-based or device-free. In case of device-based systems, humans carry a device transmitting or receiving some kind of optical (infrared, visible light), acoustic (ultrasound) or electromagnetic (WiFi, Bluetooth, Ultrawideband, Zigbee, cellular network signals, RFID) signals [147]. Those signals are then received, analyzed and processed by a central computing entity, so that the position or movement of the device can be determined.  
Active localization is based on the active participation of the device, which can measure signals from base stations or satellites (e.g., in GPS) and report back measurement results to a central system processing the measurements. This is often supported by a special software to be installed on the device. Passive localization does not require any changes in a device. Signals received by radio sensors are intercepted from regular data traffic exchanged between devices and base stations, e.g., cellular network base stations or WiFi access points.  
Both active and passive localization are often based on determining the distance between a device and some sensors or base stations, which is also called ranging. Ranging mechanisms are based on measuring received signal strengths (RSS) or time (difference) of arrival [148]. Measured distances can then be fed into positioning algorithms such as multi-lateration or geometric algorithms [149]. Alternatively angles of arrival of the signals can be measured and processed, e.g., by using triangulation algorithms.  
Activity detection can be based on tracking or just measuring the presence of a device. Device-free localization [150] does not require humans to carry a device. Cameras can detect persons. The position of the person can be detected by processing signals if the camera is moving or if there are multiple (stereo) cameras deployed.  
Human localization and activity tracking is important for providing support for disabled (e.g., people with impaired vision of blind) or older people with mental problems (such as dementia or epilepsy). Such tracking requires the use of cognitive IoT technologies. In order to provide intelligent services and intelligent decision-making, the novel sensing technologies are needed. The existing environment and its residents monitoring methods still lack precision, require obtrusive sensing technologies, which are usually not comfortable for the wearer. The economic factor is also an issue, since installation of currently available systems is expensive, requiring many and complex hardware elements deployed at residents' homes. The users feel discomfort and their homes look more like a laboratory instead of a normal living environment. Again, as in the case with IoT based decision-making technologies, the IoT concept is very promising in the field of intelligent environment and users monitoring. Since each appliance or any \"thing\" at home can be part of IoT, it is a very convenient and unobtrusive way of collecting information about residents and environment's state, which later can be used for the intelligent decision making.