An analysis of mist computing and its applications in modern technology

Following the widespread adoption of cloud computing, researchers and businesses have been developing additional approaches that bring computing closer to the end users in order to realise ground-breaking applications, provide better QoS, exert more control over sensitive data, and maximise resource reuse. So, a general definition of mist computing is the downward push of cloudy computing characteristics to sensor networking at the very edge of the network. As is customary for Internet technology trends, Mist Computing has quietly become well-known, but it still needs a lot of work and time to evolve into a clear and understood technology that changes the industrial landscape. The conventional methods have drawbacks, such as a lack of generality and a significantly slower rate of convergence. In order to address the challenge of sending enormous amounts of data to far-off cloud data centres, new computing paradigms like mist and fog computing have emerged as a result of the Internet of Things' (IoT) fast proliferation. The data is transmitted to the cloud server in the traditional setup of a GIS framework based on cloud computing, where it is processed and examined. On the Internet, this method used a lot of computing power and traffic. The Internet of Things (IoT), which consists of a network of connected sensors and devices, is continually growing. As a result, massive volumes of data of all kinds being created at speeds that were previously unheard of. Fog computing emerged as a solution to the problem of moving huge amounts of IoT data to distant cloud resources for processing by adding a layer between the IoT and cloud levels. This review paper addresses three of applications of mist computing, specifically Internet of Things, SmartHealth and Geospatial Data Analysis.