Related papers: CollabLoc: Privacy-Preserving Multi-Modal Localiza…
With the tremendous increase in the number of smart phones, app stores have been overwhelmed with applications requiring geo-location access in order to provide their users better services through personalization. Revealing a user's…
The Internet of Things (IoT) envisions billions of sensors deployed around us and connected to the Internet, where the mobile crowd sensing technologies are widely used to collect data in different contexts of the IoT paradigm. Due to the…
The rise of the Internet of Things (IoT) and mobile internet applications has spurred interest in location-based services (LBS) for commercial, military, and social applications. While the global positioning system (GPS) dominates outdoor…
Mobile crowdsensing engages a crowd of individuals to use their mobile devices to cooperatively collect data about social events and phenomena for special interest customers. It can reduce the cost on sensor deployment and improve data…
In multi-robot systems (MRS), cooperative localization is a crucial task for enhancing system robustness and scalability, especially in GPS-denied or communication-limited environments. However, adversarial attacks, such as sensor…
We consider the problem of client-server localization, where edge device users communicate visual data with the service provider for locating oneself against a pre-built 3D map. This localization paradigm is a crucial component for…
Location data can be extremely useful to study commuting patterns and disruptions, as well as to predict real-time traffic volumes. At the same time, however, the fine-grained collection of user locations raises serious privacy concerns, as…
Accurate indoor node localization is critical for practical Wireless Sensor Network (WSN) applications, as Global Positioning System (GPS) fails to provide reliable Line-of-Sight (LoS) conditions in most indoor environments. Real-world…
To date, most place recognition methods focus on single-modality retrieval. While they perform well in specific environments, cross-modal methods offer greater flexibility by allowing seamless switching between map and query sources. It…
This paper proposes a new privacy-enhancing, context-aware user authentication system, ConSec, which uses a transformation of general location-sensitive data, such as GPS location, barometric altitude and noise levels, collected from the…
Location-based queries enable fundamental services for mobile road network travelers. While the benefits of location-based services (LBS) are numerous, exposure of mobile travelers' location information to untrusted LBS providers may lead…
Object detection is an essential task for autonomous robots operating in dynamic and changing environments. A robot should be able to detect objects in the presence of sensor noise that can be induced by changing lighting conditions for…
For decades, the determination of an objects location has been implemented utilizing different technologies. Despite GPS (Global Positioning System) provides a scalable efficient and cost effective location services however the satellite…
Mobile Large Language Models (LLMs) are revolutionizing diverse fields such as healthcare, finance, and education with their ability to perform advanced natural language processing tasks on-the-go. However, the deployment of these models in…
Although people spend most of their time indoors, outdoor tracking systems, such as the Global Positioning System (GPS), are predominantly used for location-based services. These systems are accurate outdoors, easy to use, and operate…
We consider the problem of tracking a group of mobile nodes with limited available computational and energy resources given noisy RSSI measurements and position estimates from group members. The multilateration solutions are known for…
Robust localization in a given map is a crucial component of most autonomous robots. In this paper, we address the problem of localizing in an indoor environment that changes and where prominent structures have no correspondence in the map…
The rapid growth of the Internet of Things fosters collaboration among connected devices for tasks like indoor localization. However, existing indoor localization solutions struggle with dynamic and harsh conditions, requiring extensive…
Context-aware applications have been gaining huge interest in the last few years. With cell phones becoming ubiquitous computing devices, cell phone localization has become an important research problem. In this paper, we present CellSense,…
To support location-based services, vehicles must share their location with a server to receive relevant data, compromising their (location) privacy. To alleviate this privacy compromise, the vehicle's location can be obfuscated by adding…