Research Articles (Electrical and Electronic Engineering)
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Browsing Research Articles (Electrical and Electronic Engineering) by Subject "Accelerometers"
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- ItemAnimal-borne behaviour classification for sheep (Dohne Merino) and rhinoceros (Ceratotherium simum and diceros bicornis)(BioMed Central, 2017-11-21) Le Roux, Solomon Petrus; Marias, Jacques; Wolhuter, Riaan; Niesler, ThomasBackground: The ability to study animal behaviour is important in many fields of science, including biology, behavioural ecology and conservation. Behavioural information is usually obtained by attaching an electronic tag to the animal and later retrieving it to download the measured data. We present an animal-borne behaviour classification system, which captures and automatically classifies three-dimensional accelerometer data in real time. All computations occur on specially designed biotelemetry tags while attached to the animal. This allows the probable behaviour to be transmitted continuously, thereby providing an enhanced level of detail and immediacy. Results: The performance of the animal-borne automatic behaviour classification system is presented for sheep and rhinoceros. For sheep, a classification accuracy of 82.40% is achieved among five behavioural classes (standing, walking, grazing, running and lying down). For rhinoceros, an accuracy of 96.10% is achieved among three behavioural classes (standing, walking and lying down). The estimated behaviour was established approximately every 5.3 s for sheep and 6.5 s for rhinoceros. Conclusions: We demonstrate that accurate on-animal real-time behaviour classification is possible by successful design, implementation and deployed on sheep and rhinoceros. Since the bandwidth required to transmit the behaviour class is lower than that which would be required to transmit the accelerometer measurements themselves, this system is better suited to low-power and error-prone data communication channels that may be expected in the animals habitat.
- ItemPublic transport sector driver behaviour : measuring recklessness using speed and acceleration(Southern African Transport Conference, 2014-07) Zeeman, Adriaan Siebrits; Booysen, Marthinus J.The informal transport industry in Sub-Saharan Africa is notoriously dangerous, leading to many fatalities annually. This paper presents an innovative way of monitoring driver behaviour, in real-time, by taking into account road design standards and vehicle dynamics. A theoretical model is presented that combines acceleration and speed data into an erratic driving detection algorithm. The model presents a novel use of commonly used civil engineering principles, used in road design. Evaluation of the models, using actual minibus taxi data, demonstrates that it successfully detect reckless driving. An online platform is presented to visualise the tracked vehicle and the driving behaviour.
- ItemVehicle acceleration estimation using smartphone-based sensorsBruwer, F. J.; Booysen, Marthinus J.Recent advances in smartphone technology, including motion sensing and wireless communications, have resulted in these devices being used for vehicle-based driver behaviour sensing applications, replacing existing bespoke vehicle-based solutions. Acceleration is normally used as the primary indicator for recklessness. Despite the many benefits of using a smartphone to determine vehicle acceleration, the mobility of the phone relative to the vehicle, and the vehicle relative to the earth, causes the earth's gravitational force to obscure the true vehicle acceleration as perceived by the phone. The design and test results in this paper demonstrate how quaternions and an unscented Kalman filter can be used to remove the gravitational vector from the sensed acceleration, which enables reckless driving detection.