As businesses and enterprises raced to move infrastructure and applications to the cloud in 2020, some discovered the better strategy was to take computing to the edge. Edge computing enables applications to run close to where data is generated, rather than to require data to travel from the source to a data center or cloud and back, creating latency that mission-critical processes can’t tolerate. Moreover, when edge computing is used in combination with artificial intelligence (AI), edge AI can open doors to innovation, greater security and compliance, and automation.
Sastry Malladi, CTO of FogHorn and Senthil Kumar, FogHorn’s Global Head and VP of Software Engineering, expect edge AI to make a significant impact on businesses and industries in 2021, for example:
1Edge AI tools will eliminate the need to rip and replace outdated legacy building management systems.
Kumar says one of the critical obstacles holding back smart building adoption is the prevalence of outdated or legacy systems. According to a recent OMDIA survey, this is ranked as the biggest challenge for end-users when implementing IoT-enabled smart building technologies. However, without cloud connectivity for data processing or integrations with other smart building systems, building operators see costs rise over 400 percent.
“Over the next 12 months, rather than replacing a current building management system (BMS) and implementing new and costly hardware and software, building operators will install edge-enabled IoT tools to sit on top of and enhance existing systems and provide intelligent data processing capabilities,” says Kumar. “A BMS, when equipped with real-time analytics and AI, can run real-time adjustments to schedule variations, prime HVAC systems based on changing conditions, including building occupancy, weather, and energy demands.”
He adds that building operators will also apply edge AI technology to currently installed BMS to reduce energy consumption, increase occupant comfort, safety, and better utilize building assets and services of critical systems, such as elevators, fire alarms, and sprinkler systems.
2Edge AI enables contactless health and safety monitoring in the workplace.
As the pandemic continues, many businesses will continue to implement body temperature scanning solutions, often using thermal cameras or infrared technology. “Identifying elevated body temperatures within any work environment will be vital in helping protect against both COVID-19 and other illnesses, such as the flu or common cold,” Kumar explains. He adds, however, that the CDC warns against potential exposure when taking an employee or customer’s temperature via infrared thermometers.
“In 2021, organizations will leverage edge AI technology to gather the necessary data to help enforce and maintain a safe distance while screening employee or customer health while also enforcing workplace safety by restricting facility access to only those who meet the approved body temperature ranges,” Kumar says. “Furthermore, using edge AI capabilities, employees can be notified remotely and immediately as messages can be sent to employees or customers directly in real-time, versus communicating health and safety noncompliances in-person to management — risking their own health.
3Warehouse managers will implement mobile edge computing to keep up with increased orders.
Today, many warehouse and logistics operations are under pressure to significantly reduce order-to-delivery timelines. Malladi predicts organizations will deploy industrial mobile devices, equipped with specialized applications, to make it possible to meet these demands. In addition, according to GSMA Intelligence, IIoT connections will overtake consumer IoT connections in 2023, driven in part by enterprise use of mobile devices.
Malladi says, “In 2021, warehouses will pair the low-latency processing power of the edge with the mobility of handheld devices to enable real-time operational insights on mobile devices unrestricted from fixed locations or even cloud connectivity. This flexibility ensures warehouse workers are kept in the loop of all internal operations and changes at all times and without having to alter their current daily routines.”
“Furthermore, mobile edge solutions can enable workers to instantaneously share information and insights across the warehouse, ensuring that all workers are on the same page,” he adds. “Mobile edge AI enables a new class of industrial edge computing applications that empowers industrial workers to quickly identify production or environmental irregularities and correct them. This not only prevents costly machine downtime and product quality issues but also improves employee safety conditions.
4Automated safety monitoring will save businesses millions in workers’ compensation costs.
“Workplace safety has always been a priority for manufacturers, but it takes on new significance in light of the pandemic,” says Malladi. He points out that businesses paid almost $1 billion per week in direct workers’ compensation costs (pre-COVID), enabled in part by ineffective monitoring systems. “The manual nature of traditional health and safety audits means the potential for error is significant and time-consuming,” he says.
“As businesses worldwide consider back-to-work strategies for early-to-mid 2021, many will upgrade and future-proof existing worker safety systems and processes,” Malladi predicts. “Real-time, streaming data processing will reform legacy best practices, make up for the error-prone shortcomings of resource-intensive manual audits, and provide real-time insights and centralized visibility into workplace health and safety.”
Malladi predicts these solutions will include real-time processing of data collected from IoT sensors and cameras, possibly including employee temperature detected by thermal cameras, AI that detects signs that an employee is ill, and video analytics that confirms employees are socially distancing. “Rapid identification of potential health and safety hazards will enable enterprises to respond to risky situations in seconds rather than reviewing data later or waiting to scan each employee individually,” says Malladi. “These capabilities will be calibrated to monitor an organization’s specific health and safety needs, even beyond COVID-19.”
For example, industrial safety can include confirming the use of protective gear, such as safety goggles, reflective vests, and hard hats. Additionally, advanced technologies can detect potential environmental safety hazards, such as falling objects and trip hazards.
5Greater adoption of video and other high-resolution, high bandwidth sensors increases the demand for edge AI.
Digital transformation often involves installing audio, video, and vibration sensors across operations. Malladi points out, however, being able to analyze high-fidelity, high-resolution, raw machine data in the cloud is often expensive and does not happen in real-time. “Organizations often depend on down-sampled or time-deferred data to avoid significant cost constraints, and as a result, organizations miss critical insights as they’re looking at incomplete datasets,” he explains.
Malladi predicts, “In 2021, artificial intelligence capabilities at the edge will help organizations transform video data from IoT connected sensors into actionable insights in real-time.” For example, edge AI can power an autonomous defect detection system within an existing manufacturing process, or automotive manufacturers can improve road safety monitoring in autonomous vehicles.
“Edge AI will play an essential role in evaluating and delivering heightened data quality and effectiveness, as edge-enabled solutions will perform real-time analysis of voluminous data streams and identify only the most valuable insights for further processing,” Malladi says.
“We will see increasing adoption of edge AI technology as early adopters reap the benefits of real-time streaming analytics,” he says.