Location services, fundamentally, rely on two components: a mapping system and positioning system. The provides the physical map of space, identifies position within map. Outdoor location services have thrived over last couple decades because well-established platforms for both these components (e.g. Google Maps mapping, GPS positioning). In contrast, indoor haven't caught up lack reliable frameworks. Wi-Fi lacks maps is also prone to environmental errors. this paper, we present DLoc, Deep...

Bluetooth Low Energy (BLE) tags have become very prevalent over the last decade for tracking applications in homes as well businesses. These are used to track objects, navigate people, and deliver contextual advertisements. However, spite of wide interest BLE tags, primary methods them based on signal strength (RSSI) measurements. Past work has shown that such inaccurate, prone multipath dynamic environments. As a result, localization using Wi-Fi moved Channel State Information (CSI,...

A myriad of IoT applications, ranging from tracking assets in hospitals, logistics, and construction industries to indoor large spaces, demand centimeter-accurate localization that is robust blockages hands, furniture, or other occlusions the environment. With this need, recent past, Ultra Wide Band (UWB) based has become popular. Its popularity driven by its proposed high bandwidth protocol specifically designed for specialized "tags". This UWB provides a fine resolution time-of-travel...

A recent spur of interest in indoor robotics has increased the importance robust simultaneous localization and mapping algorithms scenarios. This robustness is typically provided by use multiple sensors which can correct each others' deficiencies. In this vein, exteroceptive sensors, like cameras LiDAR's, employed for fusion are capable correcting drifts accumulated wheel odometry or inertial measurement units (IMU's). However, these deficient highly structured environments dynamic lighting...

Interest in autonomous navigation and exploration for indoor applications has spurred research into Simultaneous Localization Mapping (SLAM) robot systems. While most of these SLAM systems use camera LiDAR sensors tandem with an odometry sensor, drift over time. Visual (LiDAR/camera-based) deploy compute memory-intensive search algorithms to detect 'Loop Closures' combat this drift, making the trajectory estimate globally consistent. Instead, WAIS (WiFi Assisted Indoor SLAM) demonstrates...

WiFi-based indoor localization has now matured for over a decade. Most of the current algorithms rely on WiFi access points (APs) in enterprise network to localize user accurately. Thus, user's location information could be easily snooped by an attacker listening through compromised AP. With and navigation being next step towards automation, it is important give users capability defend against such attacks. In this paper, we present MIRAGE, system that can utilize downlink physical layer...

This paper presents SSLIDE, Sound Source Localization for Indoors using DEep learning, which applies deep neural networks (DNNs) with encoder-decoder structure to localize sound sources random positions in a continuous space. The spatial features of signals received by each microphone are extracted and represented as likelihood surfaces the source locations point. Our DNN consists an encoder network followed two decoders. obtains compressed representation input likelihoods. One decoder...

Supervised learning-based sound source localization (SSL) methods have been shown to achieve a promising accuracy in the past. In this paper, MTIT, SSL for indoors using Multi-Task learning and Image Translation network, an image translation-based deep neural networks (DNNs) framework is presented predict locations of sources with random positions continuous space. We extract represent spatial features signals as beam response at each direction which can indicate chance point room. utilize...

The smart buildings of the future need to understand movement and occupancy people in environment. Using cameras provide this context can be privacy-invasive. Alternatively, installing dedicated hardware sense environment cost-prohibitive limit ubiquitous adoption. WiFi-based sensing has hence been championed building-scale sensing, as it allows for both privacy is ubiquitously deployed most buildings. However, industry-translatable research space challenging no systems WiFi data....

Wi-Fi-based indoor localization has been extensively studied for context-aware services. As a result, the accurate introduces great location privacy threat. However, existing solutions protection are hard to implement on current devices. They require extra hardware deployment in environment or modifications at transmitter receiver side. To this end, we propose DOLOS, system that can protect of Wi-Fi user with novel signal obfuscation approach. DOLOSis software-only solution be deployed...

Wide-scale adoption of VR/AR technologies in gaming, video conferencing, and for other remote telepresence applications demands limb tracking a more immersive experience. In an attempt to bolster tracking, we present UWBTrac, UWB + IMU based fusion tracker VR applications. this demo, accompanying video1, showcase comparison with HTC Vive trackers.

WiFi-based indoor localization has now matured for over a decade. Most of the current algorithms rely on WiFi access points (APs) in enterprise network to localize user accurately. Thus, user's location information could be easily snooped by an attacker listening through compromised AP. With and navigation being next step towards automation, it is important give users capability defend against such attacks. In this paper, we present MIRAGE, system that can utilize downlink physical layer...

This paper presents SSLIDE, Sound Source Localization for Indoors using DEep learning, which applies deep neural networks (DNNs) with encoder-decoder structure to localize sound sources random positions in a continuous space. The spatial features of signals received by each microphone are extracted and represented as likelihood surfaces the source locations point. Our DNN consists an encoder network followed two decoders. obtains compressed representation input likelihoods. One decoder...

Recent interest towards autonomous navigation and exploration robots for indoor applications has spurred research into Simultaneous Localization Mapping (SLAM) robot systems. While most of these SLAM systems use Visual LiDAR sensors in tandem with an odometry sensor, drift over time. To combat this drift, deploy compute memory intensive search algorithms to detect `Loop Closures', which make the trajectory estimate globally consistent. circumvent resource (compute memory) algorithms, we...