Hardware Efficient Solutions for Wireless Air Pollution Sensors Dedicated to Dense Urban Areas
| Autor: | Tomasz Talaśka, Jolanata Pauk, Marzena Banach, Rafal Dlugosz |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
air pollution sensors air pollution maps edge computing pollution data processing analog-to-digital converters low power circuits Computer science Real-time computing ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology 01 natural sciences Reduction (complexity) Base station Robustness (computer science) 0202 electrical engineering electronic engineering information engineering Wireless lcsh:Science Edge computing 0105 earth and related environmental sciences business.industry Noise (signal processing) 020208 electrical & electronic engineering Emphasis (telecommunications) General Earth and Planetary Sciences lcsh:Q business Wireless sensor network |
| Zdroj: | Remote Sensing, Vol 12, Iss 5, p 776 (2020) Remote Sensing; Volume 12; Issue 5; Pages: 776 |
| ISSN: | 2072-4292 |
| Popis: | This paper proposes novel solutions for the application of air pollution monitoring systems in so called ‘smart cities’. A possibility of the implementation of a relatively dense network of wireless air pollution sensors that can collect and process data in real time was the motive behind our research and investigations. We discuss the concept of the wireless sensor network, taking into account the structure of the urban development in cities and we present a novel signal processing algorithm that may be used to control the communication scheme between particular sensors and an external network. We placed a special emphasis on the computational complexity to facilitate the implementation directly at the transistor level of particular sensors. The algorithm was verified using real data obtained from air pollution sensors installed in Krakow, Poland. To ensure sufficient robustness of the variability of input data, we artificially added high amplitude noise to the real data we obtained. This paper demonstrates the performance of the algorithm. This algorithm allows for the reduction of the noise amplitude by 23 dB and enables a reduction of the number of wireless communication sessions with a base station (BS) by 70%–80%. We also present selected measurement results of a prototype current-mode digital-to-analogue converter to be used in the sensors, for signal resolutions up to 7 bits. |
| Databáze: | OpenAIRE |
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