SenseZero Co., Ltd. has released findings from an analysis of the effectiveness of its AI risk prediction technology, showing that proactively intercepting risk factors before accidents occur can reduce hazardous incidents at worksites (near-misses and recurring hazard factors) by up to 67%. The results demonstrate the feasibility of a shift from the traditional safety management paradigm of "responding after accidents occur" to one of "predicting and preventing before they occur."
Accidents Don't Happen Suddenly — They Accumulate
Most serious accidents are not sudden, random events. They result from hazard signals accumulating gradually until they reach a tipping point. "Small signals" build up: missing hard hats, repeated entry into hazardous zones, reduced alertness due to fatigue, frequent proximity between equipment and workers. The problem is that these signals cannot be captured in real time through human observation and manual inspections alone.
Prediction-based safety management focuses precisely on this gap. Globally, companies that have adopted AI predictive analytics have been reported to reduce accident rates by 40–50% or more, and domestically the number of worksites using AI video and big data to detect dangerous behaviors in advance — cutting safety incident rates by more than half — is growing. The center of gravity in safety management is shifting from "after-the-fact documentation" to "advance prediction."
How SenseZero's AI Risk Prediction Works
SenseZero's AI risk prediction starts by consolidating data scattered across the worksite into one place. Data is collected in real time from wearables worn by workers (location, heart rate, activity level), BLE beacons installed at the worksite (hazardous zone entry and proximity), and environmental sensors (gas, temperature, and humidity).
The collected data is analyzed across multiple risk axes — location, biometrics, behavior, and environment — and an AI Dynamic Risk Map (DRM) makes "where and how risks are accumulating" visible at a glance. Before the risk reaches the accident threshold, proactive warnings are simultaneously delivered to the manager dashboard and the worker app, creating the time needed to intervene before an accident occurs.
What "67%" Actually Means
The 67% figure validated by SenseZero through field implementation and analysis does not simply mean that accidents are reported faster. It means that recurring hazard factors can be identified through data and intercepted in advance — significantly reducing both the frequency of near-miss situations and the frequency of hazard exposure. "What is dangerous" is communicated first by data rather than by human experience and intuition.
Beyond Prediction — to "Execution" and "Evidence"
SenseZero does not stop at prediction. Safety management activities required by the Serious Accidents Punishment Act and the Occupational Safety and Health Act — risk assessments, pre-work safety briefings (TBM), safety training completion, and alert and corrective action histories — are digitally and automatically recorded and exported as evidence. Labor management and worker health management are integrated into the same platform, creating an unbroken chain that covers the full safety management lifecycle: prediction → response → documentation.
SenseZero CEO Do Yang-su stated: "The best safety outcome is not resolving an accident quickly after it happens — it is making sure the accident never happens at all. We will continue proving, through AI risk prediction, that it is possible to read hazards first and reduce industrial accidents with data."
SenseZero Co., Ltd. develops and operates an integrated industrial safety and healthcare platform specialized in accident prevention, powered by wearables, BLE beacons, and AI.
