# An Overview of Indoor Localization System for Human Activity Recognition (HAR) in Healthcare
## 6 Systems for HAR
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Technology** & **Measure Method** & **Cost** & **Advantages** & **Disadvantages** & **Accuracy (m)** \\ \hline \multirow{3}{*}{Magnetic} & \multirow{3}{*}{AOA, TOA} & \multirow{3}{*}{Medium} & \multirow{3}{*}{Medium power consumption} & Requires magnetic field mapping, errors increase with the size of the fingerprinting map & \multirow{3}{*}{\(1\)–\(3\)} \\  & & & & & \\ \hline \multirow{3}{*}{Optical} & \multirow{3}{*}{Scene analysis, proximity} & \multirow{3}{*}{Medium} & Performance improvement by fusion of image data with data from other sensors & The transformation from the image space into the object space requires additional depth information & \multirow{3}{*}{\(0.1\)} \\  & & & & & \\ \hline \multirow{3}{*}{Inertial} & \multirow{3}{*}{Dead reckoning} & \multirow{3}{*}{Low} & Great reliability, reduced size & Cumulative errors, high complexity & Error range 0.5–2\% total traveled distance \\ \cline{1-1} \cline{5-5}  & & & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: _Cont._where and what a person is doing successfully. In addition, infrastructure-based solutions use dedicated equipment installed in buildings, which increases implementation costs but produces more accurate estimates; solutions without infrastructure reduce localization accuracy with lower costs. HAR, developed to assist the elderly, can be seen according to different approaches such as health monitoring, ambient assisted living (AAL) for smart homes, and security and surveillance applications. Healthcare monitoring systems are designed to monitor the situations of individuals and provide valuable tools for emergencies. For this purpose, there are several functions, such as human tracking, fall detection, security alarm, and cognitive assistance. Wearable sensors and environmental sensors are used. Ambient assisted living (AAL) involves using AR techniques to ensure that older people in the home remain safe and lead independent lives. In a smart home, devices are user-centric and integrated into the living environment of individuals. Cameras and inertial sensors generally monitor their activities and interaction with the environment. For the elderly, it is an advantage as it helps prevent, treat, and improve their wellbeing. Figure 15 shows the architecture of a HAR system. The evolution of artificial intelligence technology has had a substantial impact on the development of forecasting models. This factor has favored using deep learning technology in constructing forecasting models within HAR systems. Their approach differs from statistical models, even though the two systems have the same aims. Both are used for forecasting and data mining. The statistical model is a mathematical function used to approximate reality. It is used to construct a data representation and to analyze any existing relationships between variables by establishing scale and significance. It is, in fact, based on the acquisition of raw data and its transformation into information that can be used to create a basis of a statistic learning model. On the other hand, machine learning is based on the ability to learn from data instead of using preprogrammed algorithms, as well as use data to build and improve forecast models and evaluate performance based on new data that has not yet been learned. Statistical models to explain the relationships between variables must use hypotheses, confidence