In one of its recent periodicals, Markets and Markets, a US-based techno-industrial research firm forecast that the global edge computing market will grow from $2.8 billion in 2019 to $9 billion by 2024. Further, it also expects a consistent migration of 75% of the Internet-enabled devices into edge-computing devices. Indeed, edge computing is the most advanced technology in the engineering and processing industries where IoT already has a strong foothold.  

Edge Computing


Though the technology was first introduced in the late 1990s, with the revolution of the Internet, today Edge computing is the uproar of Industry 4.0. It is still an emerging trend, a part of a shared processing configuration in which data collected by the sensor and calculations are carried out close to the edge – where data is produced or consumed. The engineering science refers to the most recent equipment data capture and includes high-level computational algorithms to obtain insights into data analyzed. Edge computing is also referred to as cutting-edge technology when it implies the shape of the device as sharp enough to capture data from the source and further interpret it to obtain better vision.  


Data comes from the equipment itself and is produced as the by-product of the operations of the equipment. The processing of the real-time data locally, instead of relying on cloud and streamlining day-to-day operations in the plant is edge-computing. This optimizes the need and use of internet devices and web applications by bringing computing closer to the source of the data. The analytics further ensures to build Predictive maintenance strategies before an equipment-failure.

Modern plants have machines equipped with IoT sensors and hence it is possible to send data at high speeds to cloud computing data-centers. However, transmitting all the equipment data to the cloud is unnecessary. Instead, on-board processing of the data directly at the edge facilitates the use of the additionally available bandwidth to drastically increase the number of connected sensors.

Every organization prefers to extract more data from their equipment for condition monitoring and design validation purposes. 24 X 7 data collection enables gaining an overview of equipment performance, its usage, and thus forms the basis for operational improvements.  A sound understanding of the industrial asset and its behaviour in the process (plant) can be obtained by the implementation of advanced heuristics which evaluate and predict the failure of the equipment. Typically acceleration and signal energy signals are sampled at high frequency at the edge.  

For many industrial organizations, cloud connectivity can be problematic due to the limited bandwidth of wired or mobile connections. In such circumstances, it is impractical to move all the instantaneous high-frequency machine data to the cloud. Local informatics of the equipment-statistics becomes significant and mandatory to handle voluminous data. 

Systems implementing this technology are easier to deploy and can run a wider range of applications. Security and privacy of the huge data by modern encryption methods are extremely important from the management perspective. 

Infinite Uptime’s Industrial Data Enabler (IDE), a Make In India, patented edge-computing Vibration monitoring system for Predictive Maintenance gathers triaxial vibrations, acoustics, and temperature of any mechanical rotating equipment in real-time. It assures the correct utilization of human resources on the shop floor and empowers the Maintenance team to combat the equipment damage in advance. The plug and play system with visual indicators provides insights on the dashboard and forecasts the failure of equipment/ assembly. Thus the end -to-end solution comprising of hardware, software, and firmware potentially ensures maximum uptime, reduces maintenance costs and digitizes the plant.  

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