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3 results on '"visual recognition algorithm"'

1. Emerging Electronics Technologies and Solutions for Eco-Friendly Cities.

Author

Andriukaitis, Darius, Andriukaitis, Darius, Brida, Peter, and Pan, Yongjun

Subjects
Energy industries & utilities, History of engineering & technology, Technology: general issues, EDEM, LSTM, Markov model, RecurDyn, VMD, ad hoc network, adaptive digital filter, air pollution, arrhythmia, beacon, bucket fill factor, cardiovascular system, coal thickness, communication technology, denoising, design thinking, distributed manufacturing, driving restrictions, drone, dust sensors, eco-friendly city, eco-friendly networks, energy efficiency, energy flow, excavator, fast R-CNN, functional delay and sum beamforming, heart rate, hybrid routing protocol, infectious waste, land survey, large-scale, load, loader, log-normal fading, low-power networks, material surface three-dimensional information, mathematic model, memetic algorithm, microcontroller, modeling, n/a, noninvasive method, operating data, performance enhancement, regression prediction, rescheduling, resource efficiency, seismic attribute, seismography, sound source identification, spherical microphone array, sustainability, typical working condition, unmanned vehicle, visual recognition algorithm, waste management, wireless sensor network
Abstract

Summary: The growing population is forcing us to look for new, more effective solutions to various problems. The rising demand for power, water supply and waste management, pedestrian safety, the efficient use of electric vehicles, traffic jams, commuting, the identification of all road users and prediction of their travel paths, and increasing air and noise levels are the most pressing issues in today's cities. Advance planning is a feature of green development that reduces dependence on vehicles associated with an increase in greenhouse gas emissions. The development of eco-friendly cities includes the development and application of new efficient solutions and technologies, such as efficient transport management, emission control and pollution control, energy efficiency and the usage of renewable energy, resource efficiency, etc., which would ensure a better quality of life of the growing population.

2. A Sensor-Based Drone for Pollutants Detection in Eco-Friendly Cities: Hardware Design and Data Analysis Application

Author

Roberto De Fazio, Leonardo Matteo Dinoi, Massimo De Vittorio, and Paolo Visconti

Subjects
TK7800-8360, Computer Networks and Communications, air pollution, drone, land survey, visual recognition algorithm, fast R-CNN, dust sensors, microcontroller, Hardware and Architecture, Control and Systems Engineering, Signal Processing, Electronics, Electrical and Electronic Engineering
Abstract

The increase in produced waste is a symptom of inefficient resources usage, which should be better exploited as a resource for energy and materials. The air pollution generated by waste causes impacts felt by a large part of the population living in and around the main urban areas. This paper presents a mobile sensor node for monitoring air and noise pollution; indeed, the developed system is installed on an RC drone, quickly monitoring large areas. It relies on a Raspberry Pi Zero W board and a wide set of sensors (i.e., NO2, CO, NH3, CO2, VOCs, PM2.5, and PM10) to sample the environmental parameter at regular time intervals. A proper classification algorithm was developed to quantify the traffic level from the noise level (NL) acquired by the onboard microphone. Additionally, the drone is equipped with a camera and implements a visual recognition algorithm (Fast R-CNN) to detect waste fires and mark them by a GPS receiver. Furthermore, the firmware for managing the sensing unit operation was developed, as well as the power supply section. In particular, the node’s consumption was analysed in two use cases, and the battery capacity needed to power the designed device was sized. The onfield tests demonstrated the proper operation of the developed monitoring system. Finally, a cloud application was developed to remotely monitor the information acquired by the sensor-based drone and upload them on a remote database.

Published
2021
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3. A Sensor-Based Drone for Pollutants Detection in Eco-Friendly Cities: Hardware Design and Data Analysis Application.

Author

De Fazio, Roberto, Dinoi, Leonardo Matteo, De Vittorio, Massimo, and Visconti, Paolo

Subjects
AIR pollution, AIR pollution monitoring, POLLUTANTS, DATA analysis, GPS receivers, WIRELESS sensor networks, CLASSIFICATION algorithms, RASPBERRY Pi
Abstract

The increase in produced waste is a symptom of inefficient resources usage, which should be better exploited as a resource for energy and materials. The air pollution generated by waste causes impacts felt by a large part of the population living in and around the main urban areas. This paper presents a mobile sensor node for monitoring air and noise pollution; indeed, the developed system is installed on an RC drone, quickly monitoring large areas. It relies on a Raspberry Pi Zero W board and a wide set of sensors (i.e., NO2, CO, NH3, CO2, VOCs, PM2.5, and PM10) to sample the environmental parameter at regular time intervals. A proper classification algorithm was developed to quantify the traffic level from the noise level (NL) acquired by the onboard microphone. Additionally, the drone is equipped with a camera and implements a visual recognition algorithm (Fast R-CNN) to detect waste fires and mark them by a GPS receiver. Furthermore, the firmware for managing the sensing unit operation was developed, as well as the power supply section. In particular, the node's consumption was analysed in two use cases, and the battery capacity needed to power the designed device was sized. The onfield tests demonstrated the proper operation of the developed monitoring system. Finally, a cloud application was developed to remotely monitor the information acquired by the sensor-based drone and upload them on a remote database. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

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