Patient positioning in Internet of things (IoT) healthcare application Paper

Patient positioning is one of the major challenges in Internet of things (IoT) healthcare application [23]. Positioning system based on environment could classify into indoor and outdoor positioning [32]. Since patients tracking take place [30] in hospitals or at their homes we focus on indoor positioning. Indoor positioning system (IPS) has attracted remarkable attention in recent years for positioning at indoor environment where GPS that used for outdoor positioning environment is not available or signals are degraded while passing through the walls or obstacles [27, 22, 17, 16, 15, 11]. It designed to provide information about inside a building [21]. Owing to rapid advance of embedded computing devices and improvement in sensor technologies, indoor positioning system begins more popular [17].As an application of such technologies, studies show that people spend most of their time at an indoor environment like office buildings, malls, airports and etc [26, 20, 16]. Based on this scenario accurate indoor positioning in such environment is expected. Although Global Positioning System (GPS) provide satisfactory positioning for outdoor environment, in respect to complexity of the indoor environment and satellite signal degradation by walls, ceilings, objects and other obstacles, GPS technologies is not applicable [2, 4, 5, 10, 11 ]. More over indoor environment is undergoing by non-line-of-sight (NLOF) or signal fluctuation [15]. These mentioned items could impact on signal propagation and finally reduced the positioning accuracy [1]. Hence researchers exert various technologies and techniques to cope with problem. Various technologies and other signals have been considered, Signals like cellular [9, 21], ultra wideband which can penetrate obstacles [19, 40] , Wi-Fi [15 , 19, 21, 27], Zig Bee [9, 19], Bluetooth [9, 15, 19, 21, 27], GSM [21, 33], magnetic fields [15, 19, 27] that create magnetic fingerprint to track the position , FM radio [15], Light which act by receive and detecting the LED lights[11, 13, 15, 32], inertial sensors [32], Radio-frequency identification (RFID) [9, 15], and ultrasounds [15, 19] could adopted for indoor positioning . Beside these technologies, resourceful technique exploits, such as fingerprinting [34-37] which collect RSS fingerprints and map the RSS to exact location, Trilateration [38, 39, and 46], Partial swarm [40], SLAM [41, 42], least square [43, 44] and Trangulation [45]. The main contributions of this paper are the following: (i) Combining internet of things technologies and architecture with indoor positioning system techniques for positioning, (ii) describe and represent Stress free indoor positioning with trajectory history and based on fingerprinting technique. Different indoor positioning systems have been developed. To achieve higher accuracy, many researchers still work on this topic. In [47] stress free floor plan approach introduced for fingerprinting based indoor positioning. The rest of paper is organized as follows. Section 2 gives a brief related work review and discussion. In section 3 we introduce our system. Furthermore section 4 devoted to evaluation. Finally a discussion and comparison of results is provided in section 5 and conclusion demonstrates in section 6.