By Matthew C. King, FogHorn global sales & business development manager
As the capability and availability of IoT-enabled devices continue to expand, so does the need for low-latency to enable real-time decision making. Edge computing is growing in adoption and popularity for IoT deployments to deliver the real-time responsiveness necessary for critical use cases in industries like manufacturing, oil/gas, and smart cities. Organizations are exploring edge computing to drive, for example, real-time streaming analytics and predictive maintenance applications for these industries.
How edge computing decreases critical worker safety concerns
Indeed, Gartner predicts 75% of enterprise-generated data will be created and processed outside the traditional, centralized data center or cloud by 2022, up from less than 10% in 2018. Organizations are examining many different edge-focused use cases to support the fast-growing number of connected devices (in fact, McKinsey identified more than 100 already). These emerging use cases cover a variety of industries and address a diverse selection of problems, including worker safety. Many organizations are exploring the use of connected sensor data and compute on the edge for safety-focused use cases, like the real-time tracking of worksite-safety conditions on oil rigs, surveillance, coordination, and transport tech to better mitigate emergencies in the utility sector and many more high-risk scenarios.
Let’s explore some specific examples:
Mining machines generate many terabytes of data each day, which help mining companies optimize their operations by improving safety, reducing energy consumption, streamlining processes, and increasing production. Mining is a high-risk profession, and many mining companies are (or are planning to) using autonomous machines to ensure worker safety and increase productivity. These trucks, trains and drills are equipped with embedded sensors that enable improved safety and route-optimization based on real-time vehicle and terrain data.
By utilizing edge computing, organizations can run analytics locally, close to the mining operation, and provide real-time insights without the need for constant connectivity to the cloud.
Power & water
Powerplant maintenance is a major undertaking. The unexpected failure of a steam turbine can create substantial disruption, damage and economic loss. To prevent this, more power utilities are deploying predictive maintenance to maximize the reliability of their equipment by detecting potential failures before significant problems arise. By relying on edge computing for critical latency-sensitive functions, utility companies can reduce operational delays by sending only non-critical information to the data center or cloud for analysis and get ahead of potentially dangerous issues with machinery, ensuring work environments meet the highest safety needs.
June is National Safety Month—and there’s no time like the present for organizations to reassess and evaluate the safety measures they have in place to protect their personnel. New tech innovations, such as edge computing, enable organizations to enhance safety while maintaining machinery and, even, improving outcomes.