The pandemic has shown that workplaces can be particularly challenging to curb the spread of the virus. As Sastry Malladi, CTO of FogHorn reports, edge computing, specifically edge artificial intelligence (AI), can help make up for the error-prone shortcomings of resource-intensive manual audits and provide real-time insights and centralised visibility into workplace health and safety.
The expense of manual health & safety audits
The manual nature of traditional health and safety audits means the potential for error is significant and effort is time consuming. In fact, businesses paid almost $1 billion (€0.82 billion) per week in direct workers’ compensation costs (pre-COVID), enabled in part by ineffective monitoring systems. Even without a global pandemic, workers are still subject to workplace hazards, such as falling objects and trip hazards.
Additionally, many industries have a lack of available resources to conduct manual health audits. For example, in K-12 education specifically there is already a national shortage of teachers. During the pandemic, those teachers and other school staff are now tasked with monitoring health and safety in the classroom and beyond adding to their already heavy workload.
In the current environment of global pandemic, temperature scans, monitoring social distancing and observing employee behaviour that may lead to health and safety risks is a never-ending task. In addition, these manual audits only puts additional workers at risk, as the employees that conduct the audits must come in close contact with each employee creating a greater opportunity of infection transmission.
This ubiquitous health monitoring will become the new normal for the foreseeable future, as no organisation will seek to needlessly risk the health of their workforce and few workers will vie for positions at workplaces that do not prioritise employee safety and health. Businesses that want to better keep their workers and occupants safe will need to embrace edge computing and edge AI capabilities to adequately monitor the health and safety of their workforce without unnecessary risk.
The advantages of using edge computing for health & safety monitoring
Through real-time data processing from strategically located Internet of Things (IoT) sensors and cameras, companies can collect and process employee health data from temperatures detected by thermal cameras, to coughs heard by audio sensors, to video analytics of employee work stations to monitor social distancing to help identify critical issues.
The critical component of edge computing capabilities is the hyper-efficient complex event processing (CEP) that cleanses, normalises, filters, contextualises and aligns raw streaming data at the source.
Rapid identification of potential health and safety hazards enables enterprises to respond to risky situations in seconds rather than reviewing data later or waiting to scan each employee individually. Gone are the days of auditing employee health through “people watching” or posted reminders. By embracing digitisation, employers will enable themselves to support much more sophisticated health and safety protocols.
Examples of edge-powered health & safety processes
An elevated body temperature is a tell-tale indicator of contagious illnesses like flu, colds and Covid-19. By feeding live video streams from thermal and RGB cameras into edge AI solutions, the AI technology can detect elevated employee temperatures to identify potential illnesses. In educational institutions, for example, this enables continuous monitoring of both students and staff without necessitating manual audits.
Deep learning models can be trained to isolate temperature readings from human tear ducts for increased accuracy. When AI detects an elevated temperature, it can send an automated alert via email or text to notify the appropriate personnel. Cameras feeding data into edge AI can also monitor employee social distancing to prevent the spread of communicable diseases, as well as help to ensure the use of facemasks.
Edge AI technology also can be customised to monitor an organisation’s specific health and safety needs, as one size does not fit all in this case. For example, a face mask for an oil refinery worker may vastly differ from a manufacturing factory floor worker’s policy-mandated face mask due to the varying levels of protection required in each environment. With the help of data scientist teams, organisations can calibrate their edge AI solutions to enforce their specific health and safety regulations and equipment.
Prior to the pandemic, health and safety monitoring was traditionally a manual task. However, the growing challenge posed to employers to ensure worker safety can be accurately and adequately addressed by digitised solutions, such as edge AI, that can provide granular insights into employee health by monitoring their vitals and behaviour in the workplace.
Enterprises that prioritise digitisation and deploying technological solutions to solve emerging problems will not only enable themselves to navigate health and safety risks like the COVID-19 pandemic, but also move that much closer to achieving the cutting-edge solutions of tomorrow.
The author is Sastry Malladi, CTO, FogHorn.
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