Topical Collection on "Recent Advances in Big Data Analytics for Environmental Conservation"
Deadline for manuscript submissions: 25 November 2024
Collection Editors
University of Maiduguri, Nigeria.
Email: gbengadada@unimaid.edu.ng, gbengang@outlook.com
University of Maiduguri, Nigeria.
Email: sjbassi74@unimaid.edu.ng
King Khalid University, Saudi Arabia.
Email: alasisi@kku.edu.sa
Topical Collection Information
In the past few decades, the world has been facing crucial challenges with reducing energy resources, water depletion, and environmental instability. Global organizations and environmental institutions are looking for opportunities to efficiently stabilize the use of energy, water, and the environment by conserving the available energy resources. Earlier, technology and analytics were only used for business growth and developments, but today they have extended their application for environmental conservation as well. Among various technologies evolving today, Big data analytics is one of the booming technologies implied for environmental sustainability. Protecting the environment and available natural resources is vital today, and it is believed that big data analytics is immensely helpful in accessing and predicting environmental risks and for continuous monitoring of scarce resources. Likewise, water-risk mapping tools developed from Big data Integration is able to monitor and forecast water risks at various locations helping to change the regulatory concerns. It provides efficient data on food, energy, and water demands for people to understand the need to prevent these vital resources.
Moreover, Big data analytics can open opportunities for bird conservation, anti-poaching detections, monitoring of endangered species, accelerate energy conservation, and early catastrophic detections. All these from a combined perspective point us to conserving the environment with extensive data on these ecosystems. With developments in smart sensors and smart grids deployed by Big data intelligence, we will be able to conserve energy and reduce consumption to a great extends. On the other hand, some of the recent advances in big data analytics include monitoring and managing data sets from hydroelectric power plants, wind energy systems, and photovoltaic cells to optimize the efficiency of energies and prevent leaks and loss of energies from power plants. They can control the water flow and prevent over-usage, allowing them to categorize and measure available energy. Big data is also providing efficient solutions to optimize water systems and integrate the hydro models. Energy management software’s are growing with Big data intelligence to identify energy savings potential. Smart energy and water management are possible with the ability of Big data analytics and tools. However, certain limitations need more research to mitigate them in the future. Security issues due to voluminous data, iterative processing outcomes, limitations in real-time processing, and slow processing speed of data might cause setbacks in the future of big data analytics, especially when implied for energy, water, and the environment because these sources will have to deal with tremendous satellite and sensor data. Hence, this special issue spotlights the recent advances of big data analytics for environment and energy sustainability, enumerating the limitations that need research solutions. We invite scholars and researchers to present more submissions on the topics that fall within the scope of interest:
- Role of Big data analytics for environmental sustainability
- Impact of using big data analytics for water management and conservation
- Big data intelligence for efficient use of renewable energy resources
- Optimization of environmental satellite data using Big Data and 5G integrated systems
- Effective ways to optimize energy solutions with AI and Big data models
- Emerging trends of Big data analytics for efficient energy utilization
- Evolution of smart energy management systems with IoT integrated platforms
- Big data analysis for climate change forecasting and prediction
- Big data analytical solutions for waste management and emission control
- Future of energy sector with advanced Big Data and Internet of Things