This paper introduces a review article on indoor localization techniques and technologies. The paper starts with current localization systems and summarizes comparisons between these systems in terms of accuracy, cost, advantages, and disadvantages. Also, the paper presents different detection techniques and compare them in terms of accuracy and cost. Finally, localization methods and algorithms, including angle of arrival (AOA), time of arrival (TOA), and recived signal strength (RSS) are introduced. The study contains concepts, requirements, and specifications for each category of methods presents pros and cons for investigated methods, and conducts comparisons between them.

A modified indoor path loss prediction model is presented, namely, effective wall loss model. The modified model is compared to other indoor path loss prediction models using simulation data and real‐time measurements. Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, effective wall loss model shows the best performance among other models as it outperforms 2 times the dual‐slope model, which is the second best performance. Similar observations were recorded from the experimental results. Linear attenuation and one‐slope models have similar behavior, the two models parameters show dependency on operating frequency and antenna polarization.

Millimeter-wave indoor propagation characteristics including path loss models and multipath delay spread values for systems using directional and omnidirectional antennas are presented. The performance of the four 5G candidate frequencies, 28 GHz, 39 GHz, 60 GHz and 73 GHz, are investigated in line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios using published real time frequency measurements conducted in indoor environments. Comparisons are made against simulation data obtained from the 3D Ray Tracing Wireless InSite software over Tx-Rx separations of 1.5 m to 62 m. In addition, frequency-dependent electrical properties, such as conductivity-σ and permittivity-ε, of common building materials are incorporated in the simulation. Results show material type influences propagation behavior of mm-waves due to reflections, diffractions and penetrations of walls and objects (obstacles). It is also shown that while both, the received power and delay spread decrease with increasing frequency, the number of ray paths increases.

Alternative healthcare solutions have been identified as a viable approach to ameliorate the increasing demand for telehealth and prompt healthcare delivery. Moreover, indoor ocalization using different technologies and approaches have greatly contributed to alternative healthcare solutions. In this paper, a cost-effective, radio frequency identification (RFID)-based indoor location system that employs received signal strength (RSS) information of passive RFID tags is presented. The proposed system uses RFID tags placed at different positions on the target body. The mapping of the analysed data against a set of reference position datasets is used to accurately track the vertical and horizontal positioning of a patient within a confined space in real-time. The Euclidean distance model achieves an accuracy of 98% for all sampled activities. However, the accuracy of the activity recognition algorithm performs below the threshold performance for walking and standing, which is due to similarities in the target height, weight and body density for both activities. The obtained results from the proposed system indicate significant potentials to provide reliable health measurement tool for patients at risk.

The remarkable growth in wireless communication technologies in recent times has motivated the synergy between wireless systems and medical sciences for improved healthcare services. Several emerging wireless technologies and approaches have therefore been proposed to achieve various efficient monitoring systems for health-related activities. In this paper, localisation of a patient using the ranging approach of received signal strength from passive RFID was proposed in the form of smart room. The proposed system is modelled based on a three-level intelligent model of transition, signal measurement and location sensing. The measured RSS is analysed using particle filtering algorithm as a means of localising the position of the target in indoor environments. The system was simulated in a test bed environment using wireless insite with satisfactory results. The system is aimed at achieving a non-wearable sensor approach that is unobtrusive and non-invasive for recognition of activity and location of critically-ill patients and the elderly for timely and reliable healthcare intervention.

A comprehensive study of approaches to estimation of the local average of the received signal strength (RSS) for indoor multipath propagation is presented. The effects of the required number of RSS data samples and the Euclidean distances between neighbouring samples are investigated over 1D, 2D and 3D configurations. It was found that the effect of fast fading was reduced to an acceptable level using a 2D horizontal arrangement with a relatively large spacing configuration. Further, averaging was enhanced with larger spacing compared to small spacing, when considering the same number of samples.