5 papers
Deep Transfer Learning for WiFi Localization
Peizheng Li, Han Cui, Aftab Khan +4
This paper studies a WiFi indoor localisation technique based on using a deep learning model and its transfer strategies. We take CSI packets collected via the WiFi standard channe…
Wireless Localisation in WiFi using Novel Deep Architectures
Peizheng Li, Han Cui, Aftab Khan +4
This paper studies the indoor localisation of WiFi devices based on a commodity chipset and standard channel sounding. First, we present a novel shallow neural network (SNN) in whi…
Standing on the Shoulders of Giants: AI-driven Calibration of Localisation Technologies
Aftab Khan, Tim Farnham, Roget Kou +4
High accuracy localisation technologies exist but are prohibitively expensive to deploy for large indoor spaces such as warehouses, factories, and supermarkets to track assets and…
How Agile is the Adaptive Data Rate Mechanism of LoRaWAN?
Shengyang Li, Usman Raza, Aftab Khan
The LoRaWAN based Low Power Wide Area networks aim to provide long-range connectivity to a large number of devices by exploiting limited radio resources. The Adaptive Data Rate (AD…
WiLAD: Wireless Localisation through Anomaly Detection
Cam Ly Nguyen, Aftab Khan
We propose a new approach towards RSS (Received Signal Strength) based wireless localisation for scenarios where, instead of absolute positioning of an object, only the information…