# An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare
## 7 Discussion  
The approach to this work was that of qualitative research, starting from the analysis of the state of the art of technologies, techniques, and algorithms that have carefully sought indoor positioning systems that can be applied in the tasks of localization and assistance to older adults. The completeness of the analysis was also examined from the point of view of the main evaluation metrics. Considering the requirements for home care applications that require good levels of accuracy, short return times, and less computation, it was observed that there are not many testimonies on this issue in the literature. We believe that combining location information and tracking, inertial, physiological, and environmental data can assist in creating an efficient home care system. Together with intelligent systems that can identify the activities carried out, the use of aggregate information on the positions and movements made by the elderly allows accurate monitoring of people in need of assistance. Through the combined use of this information, caregivers can assess abnormalities and deviations from habitual behaviors that may indicate a decline in the elder's abilities. The exact knowledge of the position also facilitates interventions in emergencies and avoids potentially dangerous situations. The growth in the number of elderly people in need of care who wish to continue living in their homes while maintaining their habits has stimulated the creation of increasingly innovative home care systems to avoid hospitalizations with apparent savings in care costs. New technologies with significant advances in accuracy and speed, as well as the availability of smartphones equipped with integrated technologies such as Wi-Fi, Bluetooth, IMU, and high-definition cameras, can be used to improve the quality of location systems. However, integrated systems for elderly care require performance that is incompatible with long processing times and solutions that use special devices and specialized infrastructures. Acquisition, installation, and maintenance costs must be low in order for them to be accepted by users. No solution can satisfy the use of an IPS system in all indoor scenarios. Therefore, the problem of indoor positioning requires further research to obtain cost-effective solutions with good performance. IoT technology and hybrid architectures open up a broad scenario in which designers can experiment with new approaches to fill the existing gaps. With the advent of IoT, recent technologies can provide various solutions to collect and transmit data, including location information. LTE and 5G broadband cellular networks are, in fact, suitable technologies for IoT environments. However, it must be considered in the design that the presence of heterogeneous devices significantly affects the system's performance. Innovative applications that integrate inertial sensors with wireless technologies can represent an exciting approach for scalability, accuracy, and cost. It is a solution that has the advantage of locating the position of all Wi-Fi devices without the installation of additional hardware and software, and there is no need for the line of sight. The combination of different technologies represents a valid solution to improve system accuracy. It allows using the best features of each to find the most suitable solution to satisfy the adaptability in different indoor scenarios, heterogeneity of the network components, energy consumption, and accuracy. However, the use of multiple technologies can require more memory and computational time, affecting the cost. In general, a localization network can use additional information from one or more sensors, additional data obtained from radio systems, or additional position estimates obtained from nearby references. An aspect to consider is the multipath effects and the reflection signals present during the transmission of the signal in closed environments.