How to Leverage AI, VR and IoT to Create a Safer Workplace

by | Oct 19, 2023 | Uncategorized | 0 comments

From the Verdantix Summit:

“Artificial Intelligence (AI) and the Internet of Things (IoT) are revolutionizing occupational health and safety by providing real-time monitoring and analysis of workplace conditions. AI-powered sensors can detect hazardous conditions such as toxic gases, high temperatures, and noise levels that can cause hearing loss. IoT devices can track workers’ movements and provide alerts when they enter hazardous areas or when they are in danger. These technologies can also help identify patterns in workplace accidents and injuries, allowing companies to take proactive measures to prevent future incidents. By using AI and IoT technologies, companies can improve workplace safety, reduce the risk of accidents and injuries, and ensure that employees return home safely to their families.

In this session, our speakers will share technology use cases highlighting how a specific technology has significantly improved occupational safety outcomes.”


1. AI has been one of the hottest topics over the last 12 months when we consider the general tech market. In your opinion what is your perceived value of AI related to creating stronger EHS outcomes?

We now live in the age of “big data,” an age in which we have the capacity to collect huge sums of information too cumbersome for a person to process. The application of artificial intelligence in this regard has already been quite fruitful in several industries such as technology, bankingmarketing, and entertainment and we are seeing the same in ESG and EHS.

Training: Because generative AI allows users to query unstructured data sets and receive structured and organized responses, there could be a  shift toward more user-led training—one where a new user can essentially “have a conversation” with the system (or repository of training content) to learn functionality and best practices.

Root-cause analysis: Such a system will enable operations teams to perform a root-cause analysis in real time to understand where the system is having difficulties or not meeting their expectations. For example, one will be able to directly ask the system why a particular product isn’t in the correct location instead of getting an error that it isn’t there.

Reporting: In the future, instead of enlisting business intelligence (BI) developers to create or modify operational reports, an operations or floor manager would simply tell the system to auto-generate any desired reports.

Communication and collaboration: Finally, and perhaps most importantly, generative AI will enable fulfillment teams to structure, organize, and streamline disparate data sets and knowledge across the network. This would enhance communication and collaboration to enable cost optimization and a superior customer experience. This can be anything from quickly summarizing Zoom calls to customizing slides and visuals for a specific audience.

2. What relevant applications have you seen adopted amongst the projects you have worked on or your client base?

We have been in the business of delivering software applications to customers for 2 decades. We are seeing a real value in imbedding AI into the technology we sell. We are imbedding AI not only in our EHS/ESG applications but also in the mobile applications we deliver.  We are using an embeddable AI portfolio: WatsonX, IBM’s AI and data platform designed to help enterprises scale and accelerate the impact of AI with trusted data.  AI will help our customers in predictive analysis. We are seeing use cases in the Hybrid Workplaces where AI can help in right sizing the occupancy of a building based on space reservation and shutting down floors and hence conserving energy and cost.

3. What considerations should firms evaluate before they adopt or pilot new tech?

Ask the vendors to demonstrate the use cases using your data.  Selecting an application is the easiest part of the process. Make sure the software solution works for you and not the other way around.  If you implement and expect value of AI applications, make sure data is available. SaaS and Cloud solutions provide you with the platform for implementing AI however this requires a lot of data and the benefit will be available in years to come. Setup expectations for yourself and for your managers

4. The adoption of these new data collection points is providing a much larger stream of structured data to EHS teams from a wider range of categories. We know that data is just data unless you know how to use it and why you want to use it. How should firms approach driving value across these multiple data streams?

There are five critical steps that can help any organization rise to the challenge posed by regulatory reporting: (1) Planning and Change Management, (2) Data Collection, (3) Calculations, (4) Data Quality Review, and (5) Report Preparation and Submittal. These steps represent a “Reporting Cycle” common to most organizations. 

Utilizing technology tools throughout this cycle in a purposeful and strategic manner enhances the gains in each step, ultimately reducing the time and effort necessary to prepare reports in the months before reporting deadlines. By continuously striving to adhere to the best practices identified for each of the five steps, and capitalizing on opportunities to use technology, organizations can make improvements each year on the timeliness, ease, and quality of their regulatory reports.


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