We document a feedback controller design for a nonlinear electrostatic transducer that exhibits
a~strong unloaded resonance. Challenging features of this type of transducer include the presence
of multiple fixed points (some of which are unstable), nonlinear force-to-deflection transfer,
effective spring-constant softening due to electrostatic loading and associated resonance
frequency shift. Furthermore, due to the utilization of low-pass filters in the electronic readout

  • Sensors
  • Last Updated On: 
    Thu, 05/14/2020 - 11:29

    The Here East Digital Twin was a six month trial of a real-time 3D data visualisation platform, designed for the purpose of supporting operational management in the built environment. 

  • IoT
  • Last Updated On: 
    Sat, 05/02/2020 - 07:19

    Academic spaces are an environment that promotes student performance not only because of the quality of its equipment, but also because of its ambient comfort conditions, which can be controlled by means of actuators that receive data from sensors. Something similar can be said about other environments, such as home, business, or industry environment. However, sensor devices can cause faults or inaccurate readings in a timely manner, affecting control mechanisms. The mutual relationship between ambient variables can be a source of knowledge to predict a variable in case a sensor fails.

  • Artificial Intelligence
  • Last Updated On: 
    Sun, 04/26/2020 - 09:57

    [17-APR-2020: WE ARE STILL UPLOADING THE DATASET, PLEASE WAIT UNTIL IT IS COMPLETED] -The dataset comprises a set of 11 different actions performed by 17 subjects that is created for multimodal fall detection. Five types of falls and six daily activities were considered in the experiment. Data collection comes from five wearable sensors, one brainwave helmet sensor, six infrared sensors around the room and two RGB-cameras. Three attempts per action were recorded. The dataset contains raw signals as well as three windowing-based feature sets.

  • Artificial Intelligence
  • Last Updated On: 
    Mon, 05/11/2020 - 20:12

    Dataset of V2V (vehicle to vehicle communication), GPS, inertial and WiFi data collected during a road vehicle trip in the city of Porto, Portugal. Four cars were driven along the same route (approx. 12 km), facing everyday traffic conditions with regular driving behavior. No special environments or settings were chosen, other than keeping the vehicles in communication reach of each other for as long as possible while being safe and compliant with the road rules.

  • IoT
  • Last Updated On: 
    Mon, 04/13/2020 - 14:20

    The downloadable files contain all data and associated scripts that generate results as seen in the article. The major component description and detailed setup and run instructions are also provided in the README file.

  • Geoscience and Remote Sensing
  • Last Updated On: 
    Tue, 04/07/2020 - 11:09

    Dataset of rosbags collected during autonomous drone flight inside a warehouse of stockpiles. PCD files created using reconstruction method proposed by article.

    Data still being move to IEEE-dataport. 

  • Computer Vision
  • Last Updated On: 
    Tue, 04/28/2020 - 10:22

    CUPSNBOTTLES is an object data set, recorded by a mobile service robot. There are 10 object classes, each with a varying number of samples. Additionally, there is a clutter class, containing samples where the object detector failed.

  • Computer Vision
  • Last Updated On: 
    Fri, 02/28/2020 - 11:47

    A Traffic Light Controller PETRI_NET (Finite State Machine) Implementation.


    An implementation of FSM approach can be followed in systems whose tasks constitute a well-structured list so all states can be easily enumerated. A Traffic light controller represents a relatively complex control function

  • Artificial Intelligence
  • Last Updated On: 
    Mon, 02/24/2020 - 07:47

    Dataset of GPS, inertial and WiFi data collected during road vehicle trips in the district of Porto, Portugal. It contains 40 trip datasets collected with a smartphone fixed on the windshield or dashboard, inside the road vehicle. The dataset was collected and used in order to develop a proof-of-concept for "MagLand: Magnetic Landmarks for Road Vehicle Localization", an approach that leverages magnetic anomalies created by existing road infrastructure as landmarks, in order to support current vehicle localization system (e.g. GNSS, dead reckoning).

  • Machine Learning
  • Last Updated On: 
    Mon, 03/30/2020 - 16:05