Differential barometric-based positioning technique for indoor elevation measurement in IoT medical applications

BACKGROUND: Medical applications have begun to benefit from Internet of Things (IoT) technology through the introduction of wearable devices. Several medical applications require accurate patient location as various changes affect pressure parameters inside the body. OBJECTIVE: This study aims to develop a system to measure indoor altitude for IoT medical applications. METHODS: We propose a differential barometric-based positioning system to estimate the altitude between a reference sensor and a localizing sensor connected to the human body. The differential barometric altimetry model is introduced to estimate indoor elevations and eliminate environmental artifacts. In addition, a Gaussian filter processing is adopted to remove noise from the elevation measurements. The proposed system is then investigated through extensive experiments, using various evaluation criteria. RESULTS: The results indicate that the proposed system yielded good accuracy with reduced implementation complexity and fewer costs. CONCLUSIONS: The proposed system is resilient compared to other indoor localization approaches, even when numerous environmental artifacts in indoor environments are present.