AI revolutionizes EHS processes, automating near miss reporting, housekeeping checks, PPE monitoring, and vehicle supervision. It provides accurate data for better safety management. Configuring AI systems like computer vision is user-friendly, no machine learning expertise needed.

This article outlines how to apply GDPR's data protection principles to CV technology. It emphasizes transparency, specified purposes, data minimization, storage limitation, accuracy, and integrity/confidentiality.

Surveily is a powerful EHS tool that provides data-driven insights for safety improvement. It records and stores safety events, generates reports, tags stakeholders, and enables collaboration. With real-time data and advanced analytics, EHS teams can identify trends, prevent accidents, and enhance safety performance.

In this article, we will discuss how CV can be used to measure KPIs more accurately and in real-time, providing data-driven insights that can help organizations improve workplace safety and reduce the number of workplace accidents.

In this article, we will discuss how computer vision can make warehousing and logistics safer for workers by reducing the risk of accidents.

Privacy design frameworks like Privacy by Design (PbD) ensure privacy protection. Surveily incorporates encryption, access controls, and adheres to PbD principles. While challenges exist in designing AI-based systems, organizations using privacy design frameworks demonstrate a commitment to privacy.

Workplace safety has evolved through three generations of EHS workflows. Initially reactive, it became more organized with digital incident logging. Now, the third generation focuses on proactive and predictive safety using technology like Surveily's computer vision. The goal is to achieve an injury-free workplace by identifying and mitigating risks in advance.

AI and computer vision can aid organizations in achieving OHS accreditation goals efficiently. Computer vision enables constant monitoring, feedback, and prevention of accidents (Plan stage). It also collects video clips for process assurance (Do stage) and monitors hazards and control effectiveness (Check stage). AI manages information overload and automates workflows (Act stage).

The use of AI in the EHS industry has the potential to revolutionize risk management and compliance. While concerns exist about AI replacing EHS managers, experts believe they will continue to oversee AI applications. Clear lines of responsibility and oversight mechanisms are necessary to ensure human control over AI systems.

AI technology offers solutions to challenges in near miss reporting systems. It enhances reporting by recognizing patterns and identifying hazards. AI turns CCTV cameras into real-time monitors. It fosters a just culture and involves workers in addressing causes.

Implementing a new AI safety software project can be a challenge, especially when it comes to getting approvals inside your organization. However, it's not impossible if you follow a few critical steps. In this article, we'll discuss what AI is all about and then explore five key steps to help you get senior management's support for your new AI software project.

Environmental Health and Safety (EHS) training is an integral part of many industries, aimed at minimizing hazards and risks in the workplace.