Continuous growth in software, hardware and internet technology has enabled the growth of
internet-based sensor tools that provide physical world observations and data …

In recent times, the machine learning (ML) community has recognized the deep learning
(DL) computing model as the Gold Standard. DL has gradually become the most widely …

Industrial Wireless Sensor Networks (WSNs) are becoming increasingly popular due to their
enhanced scalability and low cost of deployment. However, they also present new …

Kalman filter is a minimum-variance estimation for dynamic systems and has attracted much
attention with the increasing demands of target tracking. Various algorithms of Kalman filter …

The wide deployment of multi-modal sensors in various areas generates vast amounts of
data with characteristics of high volume, wide variety, and high integrity. However, traditional …

Traditional received signal strength indicators (RSSI's)-based moving target localization and
tracking using wireless sensor networks (WSN's) generally employs lateration/angulation …

This paper is concerned with the target tracking problem over a filtering network with
dynamic cluster and data fusion. A novel distributed consensus-based adaptive Kalman …

The Internet of Things (IoT) is widely regarded as a key component of the Internet of the
future and thereby has drawn significant interests in recent years. IoT consists of billions of …

The integration of sub-6 GHz and millimeter wave (mmWave) bands has a great potential to
enable both reliable coverage and high data rate in future vehicular networks. Nevertheless …

In fingerprint-based positioning methods, the received signal strength (RSS) vectors from
access points are measured at reference points and saved in a database. Then, this dataset …