Call for Papers
Big Data Analytics based Artificial Intelligence for Environment and Sustainability
The concept of environmental and sustainability aims to satisfy present-day needs for housing, working environments, and infrastructure without compromising the ability of future generations to meet their own needs in times to come. With the advent of the Internet of Things (IoT) and Big Data Analytics, there is a huge paradigm shift in how environmental data are used for sustainable cities and societies, especially by applying intelligent algorithms. Energy savings at BBVA’s headquarters are 5,766,731 kWh a year, equivalent to 1,900 households, which also reduces CO2 emission by a 1,430-metric ton per year. The building’s sustainable design and equipment are not solely responsible for this success: tools powered by artificial intelligence have also been used to optimize energy usage.
One of the most significant challenges facing humanity, and hence the Big Data scientist face, is not obtaining the data but properly use an existing intelligent algorithm. For example, when there is sufficient natural light coming into the work areas, the lights near the windows can adapt, reducing the light they emit, which can be achieved with a simple bio-inspired algorithm. On the other hand, with intelligent sensors measuring temperatures, air pollutants, and water poising in urban and rural areas, we can determine the precise time for adequately treating the air or water and raise an alert when certain thresholds are exceeded. These air/water treatment units are responsible for letting air/water from outside and feeding the climate control system. Artificial intelligence and green algorithms contribute to improved energy efficiency and the achievement of sustainable development goals.
This Topical Collection covers pure research and applications within the novel scopes related to sustainability computing, such as smart devices, smart homes, smart cities, smart transportation, smart environments, and smart grids will be deeply impacted by the research progress. The potential topics include, but are not limited
- Artificial Intelligence-Based Environment Quality Analysis System
- Environmental analytics using AI/Big Data technologies to increase data reliability and accuracy
- Natural inspired computing techniques for environmental monitoring
- Green computing techniques in waste management
- Applications of deep learning and unsupervised feature learning for prediction of sustainable feature smart transportation system
- AI-based Environmental sensor for air pollution monitoring and control Ambient intelligent techniques for sustainable transport
- Intelligent techniques in sustainable digital environments
- Green data analytic centers powered by renewable energy systems
- Machine Learning Methods for smart environments and urban networking Artificial Neural Network (RNN/CNN/Deep learning) for monitoring and optimization of transportation systems to improve fuel efficiency and reduce pollution
- IoT for real-time environmental awareness for firefighters
- Green Computing for Sustainable planning and city configuration evaluation
Leading guest editor
Dr. Sadia Din, School of Computer Science, Kyungpook National University, South Korea
Prof. Dr. Ouri Wolfson, Richard and Loan Hill Professor of Computer Science, University of Illinois at Chicago, USA
Prof. Dr. Carlos Alberto Kamienski, Federal University of ABC (UFABC), Brazil
Dr. Andrés Muñoz, Profesor en Grado de Ingeniería Informática/Full Lecturer in Computer Science
UCAM Universidad Católica de Murcia
Dr. Federico Cugurullo, Department of Geography, Trinity College Dublin, Ireland
Email : CUGURULF@tcd.ie
Dr.Georgios N. Kouziokas, School of Engineering, University of Thessaly, Greece
Email : firstname.lastname@example.org
Dr.Sinan Q.Salih, Department of Computer Science and Engineering, Duy Tan University, Vietnam
Deadline for submission: September 30th, 2021
How to submit?
Submit your article via Editorial Manager or by clicking on the Submit manuscript button on the home page of Environment, Development and Sustainability. Please check the Instructions for authors before submitting and select “S.I. Big Data Analytics” as Article type. In general, manuscripts should be submitted in Word and not exceed 7000 words. Environment, Development and Sustainability is a hybrid open access journal. Authors can opt to make their research open access (OA) with Open Choice if they wish. More information can be found here. Visit Springer Nature’s open access funding & support services for information about research funders and institutions that provide funding for APCs.