Indoor wireless systems often operate under non-line-of-sight (NLOS) conditions that can cause ranging errors for location-based applications. As such, these applications could benefit greatly from NLOS identification and mitigation techniques. These techniques have been primarily investigated ultra-wide band (UWB) systems, but little attention has paid to WiFi which are far more prevalent in practice. In this study, we address the problems using multiple received signal strength (RSS)...

Indoor tracking and navigation is a fundamental need for pervasive context-aware smartphone applications. Although indoor maps are becoming increasingly available, there no practical reliable map matching solution available at present. We present MapCraft, novel, robust responsive technique that extremely computationally efficient (running in under 10 ms on an Android smartphone), does not require training different sites, tracks well even when presented with very noisy sensor data. Key to...

Indoor tracking and navigation is a fundamental need for pervasive context-aware smartphone applications. Although indoor maps are becoming increasingly available, there no practical reliable map matching solution available at present. We present MapCraft, novel, robust responsive technique that extremely computationally efficient (running in under 10 ms on an Android smartphone), does not require training different sites, tracks well even when presented with very noisy sensor data. Key to...

The ubiquity of smartphones and their rich set on-board sensors has created many exciting new opportunities, where are used as powerful computing platforms to sense analyze pervasive data. One important application mobile sensing is activity recognition based on smartphone inertial sensors, which a fundamental building block for variety scenarios, such indoor pedestrian tracking, health care, smart cities. Although approaches have been proposed address the human problem, several challenges...

Indoor pedestrian positioning has been widely used in applications such as fire rescue and indoor navigation. Compared with other technologies Wi-Fi UWB, inertial measurement unit (IMU) based does not require external facilities lower cost. However, the major issue of IMU-based is that sensors exhibit errors accumulates, which affects precision. Existing techniques have reduced accumulated error, but still face several issues precision system In this paper, we propose a new technique. It...

We address the problem of localization in vehicular ad hoc networks. Our goal is to leverage vehicle communications and smartphone sensors improve overall performance. Assuming vehicles are equipped with IEEE 802.11p wireless interfaces, we employ a two-stage Bayesian filter track vehicle's position: an unscented Kalman for heading estimation using inertial sensors, particle that fuses vehicle-to-vehicle signal strength measurements received from mobile anchors whose positions uncertain,...

Pedestrian dead reckoning, especially on smart-phones, is likely to play an increasingly important role in indoor tracking and navigation, due its low cost ability work without any additional infrastructure. A challenge however, that positioning, both terms of step detection heading estimation, must be accurate reliable, even when the use device so varied placement (e.g. handheld or a pocket) orientation (e.g holding either portrait landscape mode). Furthermore, can vary over time as user...

Localization is a research area that, due to its overarching importance as an enabler for higher level services, has attracted vast amount of and commercial interest. For the most part, it can be claimed that GPS provides unparalleled solution outdoor tracking navigation. However, same cannot yet said about positioning in GPS-denied or challenged environments, such indoor where obstructions floors walls heavily attenuate reflect high-frequency radio signals. This led plethora competing...

Indoor tracking and navigation is a fundamental need for pervasive context-aware smartphone applications. Although indoor maps are becoming increasingly available, there no practical reliable map matching solution available at present. We present MapCraft, novel, robust responsive technique that extremely computationally efficient (running in under 10 ms on an Android smartphone), does not require training different sites, tracks well even when presented with very noisy sensor data. Key to...

Inertial tracking and navigation systems have been playing an increasingly important role in indoor navigation. They the competitive advantage of leveraging not requiring expensive infrastructure-only existing smart mobile devices with embedded inertial measurement units. When aided other sources information, such as radio data from WiFi/BLE infrastructure, environment constraints floor plans or maps, they often report great performance 0.5-2 m. Given promising results, what is it that...

Underground mines are characterized by a network of intersecting tunnels and sharp turns, an environment which is particularly challenging for radiofrequency based positioning systems due to extreme multipath, non-line-of-sight propagation, poor anchor geometry. Such typically require dense grid devices enable 3-D positioning. Moreover, the precise position each node needs be precisely surveyed, task in underground environments. Magneto-inductive (MI) positioning, provides orientation from...

Various applications, such as localisation of persons and objects could benefit greatly from non-line-of-sight (NLOS) identification mitigation techniques. However, techniques have been primarily investigated for ultra-wide band (UWB) signals, leaving the area WiFi signals untouched. In this study, we propose two accurate approaches using only received signal strength (RSS) measurements to identify NLOS conditions mitigate effects. We first explore several features RSS which are later...

In this paper we propose a novel algorithm for tracking people in highly dynamic industrial settings, such as construction sites. We observed both short term and long changes the environment; were allowed to walk different parts of site on days, field view fixed cameras changed over time with addition walls, whereas radio magnetic maps proved unstable movement large structures. To make things worse, uniforms helmets that wear safety them very hard distinguish visually, necessitating use...

In most sensing applications, the measurements generated by sensor networks are noisy and usually annotated with some measure of uncertainty. The question that we address in this paper is how to estimate accuracy these uncertain measurements. Existing studies on estimating real applications limited three ways. First, they tend be application-specific. Second, typically employ learning techniques parameters noise models, ignore alternative state estimation approaches without learning. Third,...

Zero Velocity Update (ZUPT) has played a key role in Pedestrian Dead Reckoning (PDR) with inertial measurement units (IMU). However, it is both crucial and difficult to determine ZUPT conditions given complex varying motion types such as walking, fast walking or running, different habits of distinct people, which have direct significant impact on the tracking accuracy. In this research we proposed model based deep neural networks moments when should be conducted. The ensures nearly identical...

Inertial navigation system (INS) is a practical method for indoor pedestrian without pre-installation of infrastructure. Based on the fundamentals human bipedal motion, zero velocity update (ZUPT) pervasive approach to tackle accumulated error inertial measurement units (IMU). While detection plays vital role in algorithm, existing fixed-threshold methods pick these pseudo-measurements error-state Kalman Filter (ESKF) have doubtful capability fit various individuals different motions. To...

map matching has played a crucial role in technologies related to indoor positioning. Conventional algorithms based on particle filter (PF) have some limitations, such as the limited use of information, poor generalization and low precision. To solve these problems, we propose an adaptable network (AdaPFnet), novel technique that integrates algorithm into neural network. AdaPFnet uses local views particles represent so information about location can be learned sufficiently through...

In this letter, we develop an exactly slot-based model for IEEE 802.15.4 protocol with sleep mechanism in real-time applications. By explicitly modeling the mechanisms and CSMA/CA a precision of slot, accurately evaluate performance protocol, including energy consumption throughput. We take into consideration impacts several factors, duty cycle, network traffic initial backoff exponent. NS-2 simulations show accuracy proposed model.

The ubiquity of smartphones and their rich set onboard sensors have created many exciting new opportunities. One important application is activity recognition based on smartphone inertial sensors, which a fundamental building block for variety scenarios, such as indoor pedestrian tracking, mobile health care smart cities. Though approaches been proposed to address the human problem, number challenges still present: (i) people's motion modes are very different; (ii) there limited amount...

Speech recognition has progressed tremendously in the area of artificial intelligence (AI). However, performance real-time offline Chinese speech neural network accelerator for edge AI needs to be improved. This paper proposes a configurable convolutional based on lightweight model, which can dramatically reduce hardware resource consumption while guaranteeing an acceptable error rate. For layers, weights are binarized number model parameters and improve computational storage efficiency. A...