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Design and Implementation of an ML and IoT Based Adaptive Traffic-Management System for Smart Cities.

Sensors (Basel, Switzerland)
The rapid growth in the number of vehicles has led to traffic congestion, pollution, and delays in logistic transportation in metropolitan areas. IoT has been an emerging innovation, moving the universe towards automated processes and intelligent man...

Development of cluster analysis methodology for identification of model rainfall hyetographs and its application at an urban precipitation field scale.

The Science of the total environment
Despite growing access to precipitation time series records at a high temporal scale, in hydrology, and particularly urban hydrology, engineers still design and model drainage systems using scenarios of rainfall temporal distributions predefined by m...

New Opportunities, Challenges, and Applications of Edge-AI for Connected Healthcare in Internet of Medical Things for Smart Cities.

Journal of healthcare engineering
Revolution in healthcare can be experienced with the advancement of smart sensorial things, Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Internet of Medical Things (IoMT), and edge analytics with the integration of cloud c...

Spatial distribution and influencing factors of litter in urban areas based on machine learning - A case study of Beijing.

Waste management (New York, N.Y.)
Littering in urban areas negatively affects their appearance, is harmful to the environment and increases pollution. It is a typical urban problem looming large upon Beijing and other megacities striving for liveability and harmony in economy, societ...

Footprint Reduction of Sensor Control Modules for Remote Portable Laboratories.

Sensors (Basel, Switzerland)
Following the automation of monitoring systems for pollution levels in cities or protected nature reserves, there comes a need to increase the autonomy of robotic vectors deployed in the field. Thus, it is important to consider the weight that these ...

Contextual Detection of Pedestrians and Vehicles in Orthophotography by Fusion of Deep Learning Algorithms.

Sensors (Basel, Switzerland)
In the context of smart cities, monitoring pedestrian and vehicle movements is essential to recognize abnormal events and prevent accidents. The proposed method in this work focuses on analyzing video streams captured from a vertically installed came...

Real-time image-based air quality estimation by deep learning neural networks.

Journal of environmental management
Air quality profoundly impacts public health and environmental equity. Efficient and inexpensive air quality monitoring instruments could be greatly beneficial for human health and air pollution control. This study proposes an image-based deep learni...

Research on the Communication Strategy of History and Culture in Shaanxi Based on BP Neural Network Model.

Computational intelligence and neuroscience
Shaanxi is one of China's most important cradles of civilization. The main vein of Chinese culture is rich history and culture, and brilliant red culture embodies the essence of socialist core values. It is still relatively weak to deeply analyze the...

Research on Artificial Intelligence Classification and Statistical Methods of Financial Data in Smart Cities.

Computational intelligence and neuroscience
In order to improve the effect of financial data classification and extract effective information from financial data, this paper improves the data mining algorithm, uses linear combination of principal components to represent missing variables, and ...

Deciphering urban traffic impacts on air quality by deep learning and emission inventory.

Journal of environmental sciences (China)
Air pollution is a major obstacle to future sustainability, and traffic pollution has become a large drag on the sustainable developments of future metropolises. Here, combined with the large volume of real-time monitoring data, we propose a deep lea...