Predictions Series: Interview with Senthil Kumar, VP of Software Engineering at FogHorn
Tell us how the COVID-19 situation has changed contactless health and safety app ecosystem.
Contactless health and safety monitoring will become the workplace “new norm” post-COVID
As many businesses continue to implement body temperature scanning solutions in response to COVID-19, often using thermal cameras/infrared technology, such practices will become the new “normal” in the coming years. 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. However, the CDC warns against potential exposure when taking an employee or customer’s temperature via infrared thermometers. In 2021, organizations will look to IoT-powered, real-time analytics, also called 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. 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 in compliances in-person to management– risking their own health.
In the coming years, scientists expect similar infectious diseases to COVID-19 to impact populations worldwide, on top of existing seasonal contagious illnesses (e.g., the flu). This will fuel the fine-tuning and increased accuracy of such health and safety monitoring technologies within organizations across every industry, including using edge AI-enabled streaming video analytics for more accurate readings and results.
What role do Managers and Industrial operators play in the achievement of Energy Goals?
Building managers and operators use real-time streaming analytics to reach 2050 zero-energy goals
Increasingly, countries and individual organizations are committing to carbon neutral operations by mid-century. However, global climate measurements do not yet reflect enough positive change to limit the global temperature increase to less than 2°C over the course of the century. Per the World Economic Forum, emissions have continued to increase at a rate of 1.5% annually. A reduction of approximately 3-6% per year over the next decade will be critical to meet the established metrics.
Buildings play a significant role in delivering a carbon neutral future, as they consume 70% of the national electricity load and account for almost 40% of the national carbon dioxide emissions. What’s more, numbers show that buildings waste 30% of the energy they consume via unnecessary lighting, heating/cooling, etc., leading to over $100 billion in operational costs per year. One of the key principles in enabling carbon neutral, also called net-zero, buildings is to ensure that buildings perform as efficiently as possible to not waste energy. Unfortunately, an alarmingly low percentage of buildings today have access to any form of real-time energy reporting, and as a result, addressing the problem of energy waste and achieving net-zero building goals with today’s building management systems (BMS) remains a challenge.
What about streaming analytics capabilities in 2021 – what are your key predictions for 2050 Energy Efficiency targets?
In 2021, building operators will implement real-time, streaming analytics capabilities to enable enterprise-wide sustainability and tracking efforts and work toward 2050 energy efficiency targets.
Your thoughts on the role of IoT and Edge Computing?
By combining the power of IoT, edge computing, and artificial intelligence (AI) technologies with legacy BMS capabilities, property operators will be able to process data from a multitude of sensors and external sources and automatically enforce the optimal heating and cooling profile and lighting for each zone, room, building or campus. This approach will allow building managers to capitalize on the most efficient energy use, reduce operational costs, and do their part in achieving 2050 zero-energy goals while ensuring occupancy comfort.
Tell us more about the role of Edge and AI tools in building management systems?
Edge AI tools eliminate the need to rip-and-replace outdated legacy building management systems
Senthil Kumar: 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 soar beyond 400%.
Over the next 12 months, to overcome this roadblock, rather than replacing a current building management system (BMS) and implementing entirely new hardware and software, which is incredibly costly, building operators will install edge-enabled IoT tools to sit on top of and enhance existing systems and provide intelligent data processing capabilities. 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. As a result, building managers can amplify legacy BMS capabilities in a cost-effective manner. In 2021, building operators will 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.
How would Automated Safety Monitoring help industrial automation projects in 2021?
Automated safety monitoring will save businesses millions in workers’ compensation costs
Sastry Malladi: Workplace safety has always been a priority for manufacturers, but it takes on new significance in light of the pandemic. Businesses paid almost $1 billion per week in direct workers’ compensation costs (pre-COVID), enabled in part by ineffective monitoring systems. Indeed, the manual nature of traditional health and safety audits means the potential for error is significant and time-consuming.
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. 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.
Through real-time data processing from strategically located IoT sensors and cameras, companies will collect and process employee health data – from temperatures detected by thermal cameras, to coughs heard by audio sensors, to video analytics of employee social distancing – to get ahead of critical issues. 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 individually scan each employee. These capabilities will be calibrated to monitor an organization’s specific health and safety needs, even beyond COVID-19. For industrial organizations, improving safety will also include ensuring the on-going use of protective gear, such as safety goggles, reflective vests, hard hats, and more. Also, these modernized technologies will be customized to detect potential environmental safety hazards, such as falling objects and trip hazards.
Warehouse managers implement mobile edge computing to keep up with 50% more orders as a result of current and post-COVID online shopping trends
Sastry Malladi: Today, many warehouse and logistics operations are under pressure to significantly reduce order-to-delivery timelines, driven by increasing consumer demand and expectations. To help organizations meet these vastly accelerated timelines and improve operational visibility, industrial mobile devices, equipped with specialized applications, will make it possible to track and manage warehouse logistics in real-time, at any location. These capabilities could not come at a better time. A total of 165 billion packages were shipped in the United States in 2019. Not surprisingly, e-commerce order growth is up 54% compared to this time last year, heavily stimulated by consumer buying shifts driven by stay-at-home orders.
Powered by enterprise-wide Industry 4.0 initiatives, the adoption of industrial handheld devices has been growing steadily over the last few years. COVID-19 has further accelerated the adoption of mobile technologies based on the flexibility and portability these types of devices enable, compared to hardwired computer and control stations that are more static and make it harder for its user to socially distance. Indeed, according to GSMA Intelligence, IIoT connections will overtake consumer IoT connections in 2023, driven in part by the opportunities battery-powered, low cost mobile devices will deliver.
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. In turn, mobile edge solutions can enable workers to more instantaneously share information and insights across the warehouse, ensuring that every worker is on the same page at all times. 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.
Increasing use of video and other high-resolution, high bandwidth sensors increases demand for edge AI
Sastry Malladi: Digital transformation is sweeping through every industry, prompting organizations to install audio, video, and vibration sensors across their operations. These video and other high-resolution, high-bandwidth devices are critical in enhancing the quality of data insights to help organizations in a wide variety of industries identify issues, challenges, and opportunities. 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 due to transport and ecosystem considerations. 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.
In 2021, artificial intelligence capabilities at the edge will help organizations transform video data from IoT connected sensors into actionable insights in real-time. 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. We will see increasing adoption of edge AI technology as early adopters reap the benefits of real-time streaming analytics. For example, by utilizing edge AI-powered analytics, industrial organizations can create an autonomous defect detection system within an existing manufacturing process – or automotive manufacturers can fast-track the road to autonomous by improving road safety monitoring.
Thank you, Senthil! That was fun and we hope to see you back on AiThority.com soon.
Senthil M. Kumar is a VP of Software Engineering at FogHorn
FogHorn is a leading developer of “edge intelligence” software for industrial and commercial IoT applications. FogHorn’s software platform brings the power of machine learning and advanced analytics to the on-premise edge environment enabling a new class of applications for advanced monitoring and diagnostics, asset performance optimization, operational intelligence and predictive maintenance use cases. FogHorn’s solutions are ideally suited for OEMs, systems integrators and end customers in vertical markets such as manufacturing, power and water, oil and gas, mining, transportation, healthcare, retail, as well as Smart Grid, Smart City and Smart Car applications.