Tracking a vehicle in real time usually requires the transmission of the geographical coordinates of its route to the Internet. As part of a partnership to develop smart cities applications, a prototype vehicle tracki...
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ISBN:
(数字)9798331509002
ISBN:
(纸本)9798331532857
Tracking a vehicle in real time usually requires the transmission of the geographical coordinates of its route to the Internet. As part of a partnership to develop smart cities applications, a prototype vehicle tracking system has been developed and evaluated. The algorithm records the geolocation of the vehicle every 30 seconds, which can lead to unnecessary coordinates being sent and the communication network being overloaded. The aim of this work is to develop an algorithm that is able to determine the location of a moving object based on its angular position. The proposed algorithm uses an inertial measurement unit sensor to determine the change of direction and is able to correctly determine the route even if a coordinate is lost. We conducted an experimental study comparing the periodic approach with angular position-based approach on a route of a public bus in the city of Toledo/PR. The results show that the angle-based algorithm reduces the number of transmitted coordinates by up to 30%.
Air pollution is one of the most important health problems causing various diseases. According to the World Health Organization (WHO), it is estimated that more than 7 million deaths are due to air pollution. For this...
Air pollution is one of the most important health problems causing various diseases. According to the World Health Organization (WHO), it is estimated that more than 7 million deaths are due to air pollution. For this reason, air quality monitoring is an important indicator for guiding public policy. However, government stations are widely scattered and their high cost makes it unprofitable to invest in higher resolution. Low-cost air quality monitoring sensors can overcome this problem, but also bring new challenges. This paper presents the development of a low-cost air quality monitoring device. The low-cost station collects the following measurements: carbon monoxide (CO), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ), ozone (O 3 ), and particulate matter. The collected data is corrected using a machine learning model and sent to the Internet in real time via the LoRaWAN protocol. Mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), linearity coefficient (R 2 ), and Pearson r were used to compare model performance. Our results show that linear models such as the Alphasense equation and linear model regression cannot accurately describe the sensor response to the reference gas sensor, whereas the RF model performs better in each metric. The performance of the RF model demonstrates the potential to improve air quality monitoring and the decision-making process.
The indoor positioning system is used to determine the location of people or objects in an enclosed space. It can be used in many applications such as navigation or even active marketing to provide a better experience...
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ISBN:
(纸本)9781665478328
The indoor positioning system is used to determine the location of people or objects in an enclosed space. It can be used in many applications such as navigation or even active marketing to provide a better experience to customers. There are various solutions to perform indoor localization. In this paper, the focus is on the use of Bluetooth Low Energy beacons to determine the position of the customer or object in the room. Therefore, the goal of this work is to use low-cost HM-10 BLE boards to test their accuracy and use as beacons. After collecting and analyzing the data, it was determined that HM-10 is a viable solution for beacons. When using the log-distance path loss model to determine distance, the experiments show variations between different HM-10 boards, suggesting the need for calibration to obtain more accurate results.
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