Edge Computing is the process of escalation of cloud computing infrastructures through data processing literally at the edge or at the source of data. Due to this, there is reduced communication between the central data center and sensors as all data analytics are performed themselves at the edge of the network on streaming data. This reduces the need for devices like data analysis or drones as you no longer need instructions to accomplish tasks.
The big data analytics take place close to sensors and Internet of Things(IoT) devices in edge computing, allowing to speed up the decision-making process that will in turn speed up the process of analysis.
Edge Computing – Possible Advantages

Edge Computing Applications reduce transmission costs with improved quality of service due to a considerable reduction in the volume of data, traffic and distance to be traveled by the data
Edge Computing removes or modifies the core computing environment thus limiting the possibility of failure
The capability of edge computing to &lsquovirtualize&rsquo will extend scalability.

Benefits of Edge Computing For Industry
Edge Computing offers several remarkable benefits for organizations. They can improve performance saving on cloud computing costs as less data needs to be sent over networks. Businesses can do without IoT with cloud computing data as such data is required for a limited period of time which leads to reduced infrastructure costs. It further helps to reduce action time and response time and at the same time preserving network resources.
For Industrial IoT applications like manufacturing, smart traffic lights or power production edge computing devices can trap streaming data to prevent anything from falling apart, avert product manufacturing defects, reroute traffic in case failing traffic lights or to optimize production. With the advent of digital transformation and emerging new technologies, we can expect everything smart in future from cars, agriculture, cities or even the health sector. Although there will be an extensive implementation of IoT sensors with edge computing, deployment can be driven easily. A good example of edge computing is Coca-Cola freestyle dispensers using edge computing to understand the behavior of customers allowing them to respond to their needs in a more efficient manner.
Edge Computing/ Fog Computing
Fog Computing does have similar goals as far as the Internet of Things is concerned with a power of computing close to the source of data like for turbines, pumps or sensors. Both Fog Computing and Edge Computing have decentralized infrastructure where data, storage, and apps are distributed efficiently between data source and cloud. Here fog networks emphasize on edge devices like IoT gateways but Edge focuses on devices connected to the ‘Thing’  like industrial machines.
Edge Computing/Cloud Computing
Edge Computing and Cloud Computing have to work together in industrial companies where enormous amounts of data are generated by machines. Both technologies can work together or independently depending on the situations. The edge dominates where speed or location is the essence and sending data from machines to the cloud becomes impossible. On the contrary cloud computing will be dominant where the requirement is considerable computing power, data volume management across planets, machine learning or general health monitoring.