Sensor Data Stream Processing in Cloud for Real-Time Decision Making

Abstract

By allowing devices to produce real-time data, the Internet of Things (IoT) is transforming several industries by providing streams that can be utilized to improve user experiences and decision-making, optimize operations, and enhance user experiences. However, handling and analyzing high volumes of sensor data in real-time is a significant challenge. With its scalability and flexibility, cloud computing is emerging as a critical enabler for sensor data stream processing. This paper explores cloud-based sensor data stream processing, emphasizing its applications, methodologies, challenges, and future directions. A thorough literature survey is presented, examining existing research on cloud solutions for real-time decision-making, focusing on platforms, frameworks, and techniques that facilitate processing high-velocity, high-volume sensor data. Moreover, it is explored how edge computing and machine learning can improve real-time analytics. The paper highlights key research gaps and future opportunities for strengthening cloud-based sensor data processing systems.