The availability of a reliable and accurate indoor positioning system (IPS) for emergency responders during on-duty missions is regarded as an essential tool to improve situational awareness of both the emergency responders and the incident commander. This tool would facilitate the mission planning, coordination, and accomplishment, as well as decrease the number of on-duty deaths. Due to the absence of global positioning system signal in indoor environments, many other signals and sensors have been proposed for indoor usage. However, the challenging scenarios faced by emergency responders imply explicit restrictions and requirements on the design of an IPS, making the use of some technologies, techniques, and methods inadequate on these scenarios. This survey identifies the specific requirements of an IPS for emergency responders and provides a tutorial coverage of the localization techniques and methods, highlighting the pros and cons of their use. Then, the existing IPSs specifically developed for emergency scenarios are reviewed and compared with a focus on the design choices, requirements, and additional features. By doing so, an overview of current IPS schemes as well as their performance is given. Finally, we discuss the main issues of the existing IPSs and some future directions.

Ultra-wideband (UWB) is a popular technology for indoor positioning systems (IPSs) due to its robust signaling in harsh environments, through-wall propagation, and high-resolution ranging. However, the propagation of wireless signals in indoor environments is affected by nonline-of-sight (NLOS) conditions, which can lead to positively biased distance estimates. Several research works were carried out in this area, but the NLOS effect caused by the human body shadowing on the ranging performance is not properly addressed in the literature. In this paper, a commercial UWB transceiver is used to assess the impact of the human body shadowing on the ranging accuracy. A set of real-time features is combined with different machine learning algorithms for NLOS identification and mitigation. With a subset of four features, a 0.97 F1-score was obtained for NLOS identification. For NLOS mitigation, with a subset of three features, the residual error follows a Gaussian distribution, has a mean error close to zero, and an STD of 0.67 m.

Sudden Infant Death Syndrome (SIDS) is one of the major causes of death among infants during their sleep. To increase the safety of the infants, we matched different emergent research fields for the development of Baby Night Watch. This Smart Wearable System (SWS), developed under the context of the European Texas Instruments Innovation Challenge (TIIC) 2015, is composed by the following elements: a Wearable IoT Device, a Gateway and the H Medical Interface. The Wearable IoT Device is a wireless sensor node integrated in a Chest Belt, and it has the capacity to monitor the following parameters: body temperature, heart and breathing rates and body position. After a minimal data processing, this set of information is sent to the Gateway, via ZigBee technology, and it is accessible to the user through the H Medical Interface. If a critical event occurs, the device will trigger an alarm, visible and audible in the proximity, and sends a distress message to a mobile application. The Baby Night Watch is an important tool for medical studies, since it allows the visualization of previous physiological data and export it to different types of datasets. Experimental tests have proven that the SWS has the potential to identify situations that could be potentially life-threatening for an infant.

Indoor Positioning Systems (IPSs) for emergency responders is a challenging field attracting researchers worldwide. When compared with traditional indoor positioning solutions, the IPSs for emergency responders stand out as they have to operate in harsh and unstructured environments. From the various technologies available for the localization process, ultra-wide band (UWB) is a promising technology for such systems due to its robust signaling in harsh environments, through-wall propagation and high-resolution ranging. However, during emergency responders’ missions, the availability of UWB signals is generally low (the nodes have to be deployed as the emergency responders enter a building) and can be affected by the non-line-of-sight (NLOS) conditions. In this paper, the performance of four typical distance-based positioning algorithms (Analytical, Least Squares, Taylor Series, and Extended Kalman Filter methods) with only three ranging measurements is assessed based on a COTS UWB transceiver. These algorithms are compared based on accuracy, precision and root mean square error (RMSE). The algorithms were evaluated under two environments with different propagation conditions (an atrium and a lab), for static and mobile devices, and under the human body’s influence. A NLOS identification and error mitigation algorithm was also used to improve the ranging measurements. The results show that the Extended Kalman Filter outperforms the other algorithms in almost every scenario, but it is affected by the low measurement rate of the UWB system.

Wireless body area networks (WBANs) comprise several sensor nodes equipped with a short range radio-frequency transceiver, implanted and/or attached to the human body. Their low form-factor and localization imply less resources available and limited energy capabilities. Therefore, energy efficiency of WBANs is a critical issue since, in many cases, batteries cannot be replaced or recharged, requiring mechanisms to extend their lifetime. The aim of transmission power control (TPC) mechanisms, which can be combined with other energy-saving mechanisms, is to reduce the energy consumption, external interferences, and specific-observation-rate in wireless communications by dynamically adjusting the transmission power output of data transmission, with the minimum effect on other performance aspects, such as reliability and latency. This paper describes and analyzes the TPCs developed as a result of a synergy created by two mechanisms, a link quality estimator and the transmission power level control. Design choices, in terms of the solutions devised to each mechanism, as well as, the strategy adopted to combine them in a TPC, are highlighted. A comparison between the newest and the most relevant research works in this area is provided as a guideline to future research. A taxonomy to classify the different TPC mechanisms developed is proposed.

Wireless Body Area Networks are being deployed for an ever increasing number of applications. The main research challenges are still related to the quality of the communication link and to the energy consumption. Since WBAN on-body communication channels’ quality varies over time, it is not appropriate to use a static and pre-defined Transmission Power Level (TPL). Nowadays, the vast majority of WBANs use Transmission Power Control (TPC) mechanisms aiming to minimize energy waste during on-body communications, radio interferences and the energy Specific Absorption Rate (SAR). These goals are achieved by continuously adjusting and updating the TPL. This paper proposes a novel TPC mechanism that employs a hybrid operation principle (closed-loop control together with Posture and Motion detection) targeting resource constrained devices. This mechanism uses the on-body communication RSSI values to approximate the fading signal during the user’s gait cycle and, simultaneously, the acceleration signal (from inertial sensors) is used to determine the position within the gait cycle. Experimental results shows that the proposed TPC mechanism is capable to achieve up to 35% energy save per packet transmitted compared to transmissions performed at maximum TPL. Furthermore, the additional traffic overhead is significantly smaller than those verified in other TPCs addressed in the literature. This research work shows that all WBAN application requirements identified by IEEE 802.15.6 TG can be ensured in an energy-efficient way without sacrificing reliability and latency.