EHS Analytics
EHS Analytics
What is EHS Analytics?
EHS Analytics refers to the systematic use of data, software, and real-time insights to monitor, measure, and improve Environment, Health, and Safety (EHS) performance in industrial environments. By collecting and analysing safety-related data from operations, equipment, workforce behaviours, and incidents, EHS Analytics helps organizations identify risks, track compliance, and make data-driven decisions to prevent workplace accidents.
In high-risk industries like manufacturing, construction, oil & gas, and logistics, EHS Analytics has become a critical tool for improving operational safety, ensuring regulatory compliance, and reducing incidents. Modern EHS Analytics platforms often integrate with IoT devices, AI video analytics, and real-time monitoring systems to deliver actionable insights for proactive safety management.
With advanced EHS Analytics, companies can track key safety indicators (KPIs), predict potential hazards, and automate reporting, transforming safety from a reactive to a predictive and preventive approach.
How does EHS Analytics improve safety performance in industrial environments?
EHS Analytics enhances safety performance in industrial environments by turning complex safety data into clear, actionable insights. By continuously collecting and analyzing data from incidents, near-misses, equipment, and workforce behaviour, EHS Analytics helps organizations detect safety gaps, predict potential hazards, and take preventive action.
In high-risk industries like construction, manufacturing, logistics, and oil & gas, EHS Analytics provides real-time visibility into safety performance through intuitive dashboards and reports. Companies can track key metrics such as incident rates, unsafe behaviours, equipment malfunctions, and environmental risks, enabling faster and more informed decision-making.
With advanced solutions that integrate AI video analytics, IoT sensors, and automated reporting, EHS Analytics allows industrial sites to shift from reactive safety management to a proactive, data-driven approach. The result is fewer incidents, improved compliance, and a safer work environment for all personnel.
What data sources are used for EHS Analytics in factories and industrial plants?
EHS Analytics in industrial plants relies on a wide range of data sources to monitor, assess, and improve workplace safety and compliance. These data sources provide real-time and historical insights, enabling organizations to detect hazards, predict risks, and enhance overall safety performance.
Common data sources for EHS Analytics in industrial environments include:
● Incident and Near-Miss Reports: Data from accidents, near-misses, and unsafe conditions recorded on-site.
● AI Video Analytics & CCTV Feeds: Visual data from AI-powered cameras for detecting unsafe behaviours, PPE compliance, and hazardous situations.
● IoT Sensors & Wearable Devices: Data from environmental sensors, gas detectors, and worker wearables to track exposure to risks, equipment status, and environmental conditions.
● Equipment and Machinery Data: Logs and maintenance records from machines to predict faults or malfunctions that could lead to safety incidents.
● Workforce Health & Safety Records: Information on training, certifications, health checks, and compliance status of workers.
Leading EHS Management platforms like viAct combine these diverse data sources through advanced Vision AI, IoT, and real-time video analytics, offering industrial businesses a unified safety monitoring system. With automated alerts, safety dashboards, and AI-powered incident detection, viAct empowers factories and plants to proactively manage risks, improve compliance, and reduce workplace incidents.
How do predictive EHS Analytics reduce incident risks on industrial sites?
Predictive EHS Analytics helps reduce incident risks on industrial sites by using real-time and historical safety data to forecast potential hazards before they occur. By analysing patterns from incidents, near-misses, equipment performance, and workforce behaviour, predictive EHS Analytics identifies safety gaps and risk trends that often go unnoticed in manual inspections.
In industrial settings like construction sites, manufacturing plants, and logistics hubs, predictive analytics leverages technologies such as AI video analytics, IoT sensors, and machine learning algorithms to detect early warning signs of unsafe conditions. This enables safety teams to take proactive measures, such as equipment maintenance, or hazard mitigation, before accidents happen.
With advanced platforms like viAct, predictive EHS Analytics becomes a practical tool for real-time risk detection and automated safety alerts. By turning raw data into actionable insights, it transforms safety management from reactive to preventive, helping reduce incident rates, improve compliance, and create safer industrial workplaces.
What are the key metrics tracked by EHS Analytics in industrial safety programs?
EHS Analytics plays a vital role in industrial safety programs by tracking key safety metrics that help organizations monitor risks, improve compliance, and enhance overall workplace safety. By leveraging real-time data and advanced analytics, companies can gain clear visibility into safety performance across their operations.
Common safety metrics tracked by EHS Analytics in industrial environments include:
● Total Recordable Incident Rate (TRIR): Measures the number of recordable incidents per 100 workers, providing a snapshot of overall safety performance.
● Lost Time Injury Frequency Rate (LTIFR): Tracks the frequency of injuries that result in lost work time, helping assess the severity of incidents.
● Near-Miss Reporting Rates: Captures the number of reported near-misses to identify potential hazards before they lead to actual incidents.
● PPE Compliance Rates: Monitors the correct usage of personal protective equipment through AI video analytics and real-time detection.
● Unsafe Behaviour & Hazard Detection: Tracks the occurrence of unsafe acts or hazardous conditions detected on-site using video analytics and IoT sensors.
With platforms like viAct, these metrics are tracked automatically through Vision AI, IoT integrations, and real-time dashboards, enabling safety teams to make informed, proactive decisions to reduce incidents and maintain a safe industrial work environment.
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Article by
Barnali Sharma
Content Writer
Barnali Sharma is a dedicated content contributor for viAct. A university gold medalist with an MBA in Marketing, she crafts compelling narratives, enhances brand engagement, and develops data-driven marketing campaigns. When she’s not busy working her content alchemy, Barnali can be found commanding stages with her public speaking or turning data into stories that actually make sense -because who said analytics can’t have a little creativity?