Indoor environment model reconstruction has emerged as a significant and challenging task
in terms of the provision of a semantically rich and geometrically accurate indoor model …

We present CrossSense, a novel system for scaling up WiFi sensing to new environments
and larger problems. To reduce the cost of sensing model training data collection …

The WiFi-based fingerprint indoor-positioning system has attracted increasing interest from
industry and academia, benefiting from the widespread deployment of the wireless local …

Device-free passive detection is an emerging technology to detect whether there exist any
moving entities in the areas of interest without attaching any device to them. It is an essential …

Received signal strength indicator (RSSI)-based fingerprinting is a widely used technique
for indoor localization, but these methods suffer from high error rates due to various …

Most of existing indoor navigation systems work in a client/server manner, which needs to
deploy comprehensive localization services together with precise indoor maps a prior. In this …

The weighted K-nearest neighbor (WKNN) algorithm is the most commonly used algorithm
for indoor localization. Traditional WKNN algorithms adopt received signal strength (RSS) …

This paper focuses on improving indoor Wi-Fi localization by mitigating the effect of
fluctuation of received signal strength indication (RSSI). The RSSI data collected at each …

Seamless outdoor-indoor positioning plays a critical role in many emerging applications, eg,
large-coverage user navigation in cities, smart buildings, and analytics of user spatial …

Indoor/outdoor localization topic has gained a significant research interest due to the wide
range of potential applications. Commonly, the Fingerprinting methods for spatial …