Applications and Perspectives of Real-Time Data Collection in Sensor Networks

Dear Colleagues,

Real-time data collection in sensor networks is a crucial aspect of modern intelligent systems, enabling advanced decision-making, automation, and monitoring across domains such as healthcare, smart cities, industrial automation, and environmental surveillance. As sensor technologies and edge computing continue to evolve, there is a growing need for novel methodologies, frameworks, and architectures to enhance the efficiency, accuracy, and scalability of real-time data collection and processing.

This Special Issue aims to present state-of-the-art research on real-time data collection in sensor networks, highlighting emerging technologies, innovative applications, and future perspectives. It will cover key topics including, but not limited to, the following:

• Advanced sensor network architectures for real-time data collection;
• Edge and fog computing techniques for efficient data aggregation;
• AI-driven data processing and decision-making in sensor networks;
• Energy-efficient protocols and low-power communication in real-time applications;
• Data compression and transmission strategies for high-speed sensing networks;
• The integration of IoT and cloud computing for real-time sensor analytics;
• Security and privacy challenges in real-time data collection;
• Real-world case studies and industrial applications of real-time sensor networks;
• Machine learning and deep learning approaches for real-time data analysis;
• Emerging trends in multimodal sensor data fusion;
• Applications in healthcare, environmental monitoring, and smart cities.

This Special Issue will serve as a valuable platform for researchers, industry professionals, and academics to present their latest findings and foster collaborations on cutting-edge developments in real-time sensor networks.

Dr. Shabir Ahmad
Guest Editor

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