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The head of IoT2US Lab, Stefan Poslad has been recognised as being in the top 2% of the world’s scientists

A comprehensive list was recently released by Stanford University and Elsevier which examined the work of more than seven million scientists across 22 subject fields between 1996 and 2019. The list considered various factors including; number of citations; h-index and

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IOT2US Lab Won the 2nd Place in IPIN2020 Competition

Introduction of IPIN Competition Indoor Positioning and Indoor Navigation (IPIN) is the largest international academic conference in the field of indoor positioning over the world. It was initiated by Federal Institute of technology, Zurich in 2010. Additionally, IPIN also holds

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QMUL IoT2US Lab CSC PhD Recruitment 2021

Who may be interested to do a CS PhD at Internet of Things Lab of QMUL with Stefan Poslad, Associated Professor, websites: http://iot.eecs.qmul.ac.uk/ http://iot.eecs.qmul.ac.uk/people/academic/stefan-poslad/ Interests: Internet of Things (IoT), Ubiquitous Computing or Pervasive Computing: Smart Devices, Environments and Interaction (SmartDEI

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IoT2USLab Research on “Bio-Internet of Things” was Reported by MIT Technology Review

IoT2USLab Research on “Bio-Internet of Things” was Reported by MIT Technology Review: The scientists who are creating a bio-internet of things Imagine designing the perfect device for the internet of things. What functions must it have? For a start, it

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IOT2US LAB WON 3RD PLACE IN THE PREMIER COMPETITION OF Indoor Positioning and Indoor Navigation (IPIN)

IoT2US Lab won 3rd place in the premier competition of the 10th International Conference on Indoor Positioning and Indoor Navigation (IPIN). There are fifteen teams in all from top universities, institutes and high-tech companies all over the world. This is

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QMUL IoT2US Lab CSC PhD Recruitment 2020

Who may be interested to do a CS PhD at Internet of Things Lab of QMUL with Stefan Poslad, Associated Professor, websites: http://iot.eecs.qmul.ac.uk/ http://iot.eecs.qmul.ac.uk/people/academic/stefan-poslad/ Interests: Internet of Things (IoT), Ubiquitous Computing or Pervasive Computing: Smart Devices, Environments and Interaction (SmartDEI

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Magnetic-field (MF) IPS

Objectives: Create an IPS that is unaffected by moving humans, providing more time-invariant location information, unlike Wi-Fi, Bluetooth Method: Use smart phone to create a radiomap of known MF patterns, then detect a new unknown RF pattern & derive the

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Prediction of People Density Distribution

Objectives: using deep learning method to predict spatial-temporal distribution of people based on the Call Detail Record (CDR) dataset Method: Use CDR to map the dynamic people density distribution by kernel density estimation (KDE) method, and then input to a

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Wi-Fi RTT Positioning System

RTT Measurement Approach An RTT range system requires an initiator to send an FTM request and a responder to respond to it with an acknowledgement (ACK). A complete callback will return four time points t1 ~ t4. The RTT is

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Millimetre Wave Radar based HAR System

Objectives: use millimetre wave radar to build a HAR system that can recognize human activities and vital signs. Method: Signal processing algorithms (e.g. FFT, Wavelet transform) are used to get feature map and machine learning and deep learning algorithms are

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