4 Top Data Analytics Startups Impacting Industrial Workplace Safety StartUs Insights

4 Top Data Analytics Startups Impacting Industrial Workplace Safety

We analyzed 240 data analytics startups impacting industrial workplace safety. StrongArm Tech, Deep Eyes, Density, and Hubble are our 4 picks to watch out for. Learn more in our Global Startup Heat Map!

Our Innovation Analysts recently looked into emerging technologies and up-and-coming startups in Industry 4.0. As there are a lot of such startups working on various different applications, we want to share our insights with you. Today, we take a look at 4 promising data analytics startups impacting industrial workplace safety.

Heat Map: 4 Top Data Analytics Startups

For our 4 top picks, we used a data-driven startup scouting approach to identify the most relevant solutions globally. The Global Startup Heat Map below highlights 4 interesting examples out of 240 relevant solutions. Depending on your specific needs, your top picks might look entirely different.


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Which startups develop the other 236 solutions?


StrongArm Tech – Predictive Analytics

Workplace injuries are a major cause of concern in manufacturing facilities and warehouses. They are a drain on the resources and may even lead to high attrition rates if left unchecked. Sprains, pains, and lacerations are among the most common types of injuries. Thankfully, all of them are preventable. Smart wearables monitor the movement of workers and predict injuries before they occur.

The US-based startup StrongArm Tech develops a lightweight Internet of Things (IoT) enabled risk monitoring device. The device collects data on multiple ergonomic and environmental factors for each worker throughout the day. The data is used by FUSE, their proprietary platform, to understand the factors that correlate with injuries. The platform intervenes when it detects an injury risk and can be used to plan safety and deployment decisions.

Deep Eyes – Video-Based Artificial Intelligence (AI)

Most workplace injuries happen because a worker isn’t wearing proper safety gear or makes erroneous movements while performing an operation. Traditionally, supervisors monitor work on screens so that they can intervene if they notice a safety violation. It is almost impossible to have eyes everywhere all the time. Technologies that can analyze video feed to detect mistakes are a solution to this challenge.

The German startup Deep Eyes develops artificial intelligence algorithms for industrial workplace surveillance. Cameras equipped with their technology monitor and alert if workers fail to wear proper gear or assume a wrong posture while operating a machine. They also notice if parts are assembled correctly, but do not store any biometric data of the workers.

Density – Space Analytics

Tailgating poses several threats to workspaces, including physical theft, property damage, intellectual property theft, and physical violence. It is a concern both when an outsider trespasses a workplace and when an employee is in an area they are not authorized to be in. Space utilization analytics determine how many people are in an area and, thus, detect if any unwanted personnel are present.

The US-based startup Density develops Class 1 infrared lasers that run machine learning algorithms to accurately count people in real-time. Their solution responds immediately to a tailgating incident and prevents the entry of unauthorized people. It can also accurately map the occupancy of each room, floor or building, a feature that can prove useful in case of an emergency. It is better than cameras, more cost-effective than turnstiles, and easy to install and scale.

Hubble – Smart Construction

Construction sites rank among the highest workplaces for workers injuries, many of them fatal. Some of the hazards of working in construction are heavy machinery, working at height, moving objects, and asbestos. Failure to communicate or comply with permit-to-work (PTW) clearances also leads to avoidable accidents. With data analytics, construction companies can monitor the safety of project sites in real-time, improve safety, and minimize costly delays.

Hubble, a startup based out of Singapore, develops a safety management module that incorporates manpower, machinery, and materials data. The module monitors all permits to work (PTW), inspections, and incidents in real-time and evaluates safety performance. In case of safety failures, it can issue non-conformity reports, revoke PTW, or impose fines on contractors, depending on the severity of the breach.

What About The Other 236 Data Analytics Startups?

While we believe data is key to creating insights it can be easy to be overwhelmed by it. Our ambition is to create a comprehensive overview and provide actionable innovation intelligence for your Proof of Concept (PoC), partnership, or investment targets. The 4 data analytics startups showcased above are promising examples out of 240 we analyzed for this article. To identify the most relevant solutions based on your specific criteria and collaboration strategy, get in touch.

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