# Human Activity Recognition for Assisted Living Based on Scene Understanding
## 3 Human Activity Recognition in the SmartCare System  
The ICT solution for assisted living proposed in [37] is improving living conditions of the elderly and/or people with chronic disorders through intelligent automation of the environment (home) and monitoring their vital parameters. Home care assistance provides independent living for the categories of people mentioned above. The SmartCare system provides a platform for monitoring, automation, and an alerting protocol in case of life-threatening events. It is a system based on heterogeneous IoT devices which offers access to data services and performs offline analysis using artificial intelligence. The Ambient assisted living system integrates software utilities in order to configure and adapt it to the needs of the beneficiary and make it easily scalable for the designer and the integrator.  
To achieve maximum user satisfaction, the SmartCare project [37] is based on a user-centric design that covers all the needs and preferences of the beneficiary, integrator or system administrator.  
As described in [37], the ambient assisted living system consists of three main parts:  
* Gateway: Implements the communication and interfaces with the installed telemedicine devices, actuators, as well as with the video monitoring component;
* Expert System: Cloud service that implements the intelligent processing of information from the sensor network and other stand-alone components by defining and following predefined monitoring and alerting rules;
* DeveloperUI: Graphical user interface that facilitates the design of solutions for specific home care applications. The patient's needs differ from case to case, according to the medical conditions.  
In Figure 1, a conceptual architecture of the SmartCare system is presented with the components mentioned above. Among the devices layer it is integrated as well the human activity recognition component using video monitoring, sub-system which communicates with the Gateway.  
The purpose of HAR is to identify the patient's life-threatening events such as falls, fainting or immobility, as well as activities which have to be regularly carried out in order to avoid critical situations, for instance people with diabetes have to serve the meal after a schedule and hydrate continuously. Failure to detect the patient for a longer period of time than a predetermined threshold and the detection of specific activities will generate warnings or notification messages to the caretaker.  
The device network is composed of sensors belonging to three main categories: vital parameters (heart rate wristband, glucose meter, blood pressure monitor, body thermometer, pulse oximeter, etc.), home automation (smart switch, smart plug, smart lock, panic button, smart lightbulb, etc.) and physical activity (video monitoring and accelerometer--steps,  
The functional diagram of the system from the perspective of the proposed HAR module is presented in Figure 3: the ZED stereo camera is connected via USB 3.0 to the Jetson unit; the events (activities of interest for the specificity of the monitored person or a life-threatening situation) are sent over MQTT to the Gateway. It is necessary to install the SDK provided in order to make use of all the image post-processing facilities of the ZED sensor. For reasons of modularity but also to relieve the gateway component of the video processing, this task is implemented on a System-on-Chip platform, Nvidia Jetson Xavier AGX. Object detection, human-object interaction detection and activity detection are also performed on Jetson.