相关论文: Smartphone-based user positioning in a multiple-us…
In this paper, we study the user localization and tracking problem in the reconfigurable intelligent surface (RIS) aided multiple-input multiple-output (MIMO) system, where a multi-antenna base station (BS) and multiple RISs are deployed to…
Due to the large bandwidth available, millimeter-Wave (mmWave) bands are considered a viable opportunity to significantly increase the data rate in cellular and wireless networks. Nevertheless, the need for beamforming and directional…
Wearable and IoT devices requiring positioning and localisation services grow in number exponentially every year. This rapid growth also produces millions of data entries that need to be pre-processed prior to being used in any indoor…
We present a human state estimation framework that allows us to estimate the location, and even the activities, of people in an indoor environment without the requirement that they carry a specific devices with them. To achieve this "device…
Proximity detection in indoor environments based on WiFi signals has gained significant attention in recent years. Existing works rely on the dynamic signal reflections and their extracted features are dependent on motion strength. To…
Wireless earbuds are an appealing platform for wearable computing on-the-go. However, their small size and out-of-view location mean they support limited different inputs. We propose finger identification input on earbuds as a novel…
Bluetooth Low Energy systems are one of the most popular solutions used for indoor localization. Unfortunately their accuracy might not be sufficient for some of the applications. One way to reduce localization errors is hybrid positioning,…
Accurate smartphone localization (< 1-meter error) for indoor navigation using only RSSI received from a set of BLE beacons remains a challenging problem, due to the inherent noise of RSSI measurements. To overcome the large variance in…
With robots increasingly integrating into human environments, understanding and predicting human motion is essential for safe and efficient interactions. Modern human motion and activity prediction approaches require high quality and…
This study describes a UWB and Machine Learning (ML)-based indoor positioning system. We propose a simple mathematical strategy to create data to reduce the job of measurements for fingerprint-based indoor localization systems. A…
Digital contact tracing is being used by many countries to help contain COVID-19's spread in a post-lockdown world. Among the various available techniques, decentralized contact tracing that uses Bluetooth received signal strength…
This paper presents a mobile crowdsensing approach to identify the indoor points of interest (POI) by exploiting Wi-Fi similarity measurements. Since indoor environments are lacking the GPS positioning accuracy when compared to outdoors, we…
Smart factories leverage advanced technologies to optimize manufacturing processes and enhance efficiency. Implementing worker tracking systems, primarily through camera-based methods, ensures accurate monitoring. However, concerns about…
While it is often critical for indoor-location- and proximity-aware applications to know whether a user is in a space or not (e.g., a specific room or office), a key challenge is that the difference between standing on one side or another…
Locating the persons moving through an environment without the necessity of them being equipped with special devices has become vital for many applications including security, IoT, healthcare, etc. Existing device-free indoor localization…
This paper describes the development of a cost-effective yet precise indoor robot navigation system composed of a custom robot controller board and an indoor positioning system. First, the proposed robot controller board has been specially…
The proliferation of wireless localization technologies provides a promising future for serving human beings in indoor scenarios. Their applications include real-time tracking, activity recognition, health care, navigation, emergence…
This paper advances the field of pedestrian localization by introducing a unifying framework for opportunistic positioning based on nonlinear factor graph optimization. While many existing approaches assume constant availability of one or…
The widespread use of smartphones gives rise to new security and privacy concerns. Smartphone thefts account for the largest percentage of thefts in recent crime statistics. Using a victim's smartphone, the attacker can launch impersonation…
Robots often use feature-based image tracking to identify their position in their surrounding environment; however, feature-based image tracking is prone to errors in low-textured and poorly lit environments. Specifically, we investigate a…