# Socially Assistive Robots in Smart Environments to Attend Elderly People--A Survey
## 3 The Use of SAR in AAL Ecosystems
### Expected Services  
The robot deployed in an AAL can assume the role of being the interface to the rest of the system. For instance, this is the case in the proposal by [PERSON] and [PERSON] [44], where the user communicates with the robot to access and control devices/information appliances in the smart home. Similar use cases are identified in [40; 41; 42]. But there are, of course, many other roles or functionalities that such robots can take on.  
In general, to identify what services people expect from service robots, previous work used interviews that were conducted by asking a series of questions to the people involved, often after a controlled demonstration, to show examples of the robot's capabilities [58; 59]. Other work conducted focus group interviews, directly asking potential users to describe the functionality that could be expected from these platforms [60; 61; 62]. This second approach also included demonstrations, usually with limited autonomy [63; 64]. In the end, only a limited set of these identified functionalities have been implemented in SARs. In the aforementioned MORPHIA project [51], the robot is used for closing the communication gap between users and caregivers. Thus, elderly people can use the robot to communicate via video or chat with relatives, friends, or caregivers. The robot can remind users to take medication or to transport meals or personal items within the home (as the Turtlebot robot deployed in the RmR AAL ecosystem [55]). When an incoming call comes in, the robot can look for the user. Relatives living far away can use an intelligent remote control to keep an eye on things in the home or support them in certain activities via telepresence. In other proposals, the robot acts as a virtual therapist, which proposes the user physical or cognitive activities [15; 40; 41; 42; 65]. Similarly, the robot can stimulate the user it accompanies to perform everyday activities [66]. Other functionalities are fall detection [67], meal assistance [68], or information and stimulation through messaging. In the aforementioned ALMI project, the TIAGo robot uses both its speech interaction for voice instructions and its object manipulation capabilities to help a user with mild motor and cognitive impairments prepare a meal. Speech interaction is also the main functionality deployed by the robot in the proposal by [PERSON] et al. [69]. In the RiSH proposal [70], human body activity recognition is addressed using inertial measurement units (IMU) and a home service robot that perceives the environment through audio signals. The applications that are provided are human position tracking and human activity monitoring. The recognition of activities, normal or abnormal, is also the service provided by the AAL environment and the robot in [PERSON] et al. [71]'s work. The proposed framework includes long-term memory models (LSTM) as well as reasoning based on Probabilistic Answer Set Programming (PASP).  
The different services offered often involve monitoring certain variables. Sometimes, the parameters monitored are related to activity recognition. This is, for example, the case in the proposals by [PERSON] et al. [70] or [PERSON] et al. [71]. Daily activities carried out are also monitored in the proposals by [PERSON] et al. [25] or in the Living at Home project [36]. The monitoring of falls, either their possible prediction or their detection, is present in numerous studies [26; 27; 28; 67]. In the EnrichMe project, body temperature, heart rate, and breathing are monitored [33]. Similar parameters are evaluated to determine the state of health in the solution provided by the [PERSON] group [35]. The early mild cognitive impairment is analyzed in the MoveCare project [15]. Finally, less emphasis is placed on the monitoring of environmental parameters (e.g., indoor air quality [53]).