AI is a pure hype in the world of technologies. Yet, this enormous popularity is justified: AI provides opportunities not only to individuals but also to business, society, and government. Evolving at a rapid pace, it revolutionizes every corner of every industry. The majority of business executives cannot afford to neglect AI and simply have to implement it if they want to be competitive over time.

Artificial intelligence is an extremely wide area of computer science that first emerged in the 1950s and by the 2000s had already found its use in such tech giants as Google, Apple, and Amazon. Essentially, AI refers to the ability of a machine or computer to perform tasks that require human intelligence, like decision-making, machine learning, natural language processing, and visual perception. AI is an umbrella term that combines machine learning, computer vision, natural language processing, data mining, chatbots.

This technology has a sheer scope of applications and can be used to perform complex work or accomplish specific business tasks depending on the requirements of the company. As a company that has built a partnership with one of the EHS leaders, Cority, we are sure that this business sector can benefit from the implementation of AI immensely.

AI Business Case 2021




    AI IN ENVIRONMENT, HEALTH & SAFETY

    Environment, Health & Safety (EHS) is a set of processes, rules, standards, and regulations aimed at the protection of the environment, company employees, and society from any damage.

    Today organizations and governments pay close attention to EHS issues, putting a lot of effort into the improvement of the sustainability of health and safety performances in the workplace. The major EHS risks businesses face today can be divided between regulatory compliance risks, occupational hazards, natural disasters, employee safety hazards, and risks caused by environmental impact.

    Here are the areas of EHS that can be significantly improved with the help of AI

    ai in EHS



    The growing risk of environmental damage due to companies’ poor compliance, in the long run, brings about tougher regulations and pressure on industries to make companies more sustainable, thus nudging them to hire more consultants and managers, increase investments in EHS management and look for more effective solutions in order to enhance the compliance.

    USE CASES OF AI FOR EHS

    These are just some of the use cases we are offering solutions for as we have relevant experience working in IT development for EHS for more than 10 years already.

    • MACHINE LEARNING FOR ANOMALIES DETECTION FOR EMISSION TRACKING

    AI has already entered the EHS industry, providing a significant number of benefits and improvements. First of all, it is possible to improve existing systems with AI, Machine Learning, or Deep Learning to get more valuable insights from the data inside the system.

    Let’s take an environmental impact as an example. Many companies are obliged to follow strict environmental regulations. Enhancing existing systems with AI, will mean that the system will analyze sustainability data and then compare them to prescribed parameters in order to detect errors or areas that are to be considered more effectively compared to analysts. More than that, it will “learn” consuming the data, and therefore, become smarter when detecting errors next time. The same principle can be applied

    Such systems are also able to alert if thresholds are exceeded or some anomaly is detected. This allows engineers, compliance managers, or chemists to focus on problems rather than waste time checking the areas which the AI-system indicates as non-problematic.

    artificial intelligence in EHS
    • PREDICTIVE-BASED SAFETY: MACHINE LEARNING, DEEP LEARNING

    Another sector where AI proves its efficiency is predictive-based safety. Based on the data it generates, AI systems can provide recommendations and forecast any failures or accidents. It’s impossible to overestimate this opportunity in a risky environment. AI-based technology can improve emissions monitoring, water quality management, waste management, and incident management, enhancing efficiency, reducing costs, and managing time and resources more effectively.

    Leading EHS software providers have already implemented various AI tools, such as data mining and machine learning, to improve a company’s key figures. With the help of data mining tools, EHS software developers solve the problem of the inefficient use of the emission credits that routinely results in halting the production. AI technologies allow to track operational processes and monitor emissions in order to detect problematic areas and anomalies in real-time. On the basis of the input data, an AI-based predictable operational model can estimate emissions, identify warning signs of potential problems, and preemptively resolve them before they occur, minimizing human intervention. 

    • СOMPUTER VISION AND MACHINE LEARNING FOR PERSONAL PROTECTIVE EQUIPMENT MONITORING

    Using the possibilities of computer vision and machine learning it is possible to control PPE wearing among the employees.

    AI for EHS sector

    By using real-time video analysis and machine learning, AI software provides monitoring of employee safety gear. By tracking entry and exit to the working environment, the system is able to assess the suitability of workers’ personal protective equipment (PPE). If an employee doesn’t comply with the requirements (forgets to put on headwear, glassware, and footwear), the system will signal and the access to the workplace will be denied till the person is properly equipped. Such a system allows to avoid human errors and enhances higher employee safety in comparison with manual PPE checks.

    Nick Chrissos, head of innovation technology at Cisco, said:

    “In any environment with increased risk, safety becomes paramount – whether physical or virtual. The application of digital technologies and applied artificial intelligence has the potential to impact the welfare and productivity of workers across many industries, whether in laboratories, construction or for critical infrastructure providers. ”

    • COMPUTER VISION FOR COLLISION PREVENTION

    Many accidents happen because of the collision of employees with the vehicles. Using the possibilities of computer vision it is possible to reduce the risk of this type of accident to the minimum. Using the data obtained from cameras at the factories, construction objects, oil& gas areas, it is possible to instantly detect if an employee is near any dangerous equipment and vehicle and notify him/her about it with the help of a signal.

    Artifical intelligence for EHS industry

    TOP AI TECHNOLOGIES WE USE FOR EHS


    Machine Learning (ML) is a sub-field of AI that allows computers or devices to learn from the input data without human intervention. The machine learning algorithms are able to adjust to the new data and constantly improve themselves due to specially programmed algorithms. This technology can help the EHS industry to enhance the decision-making processes, reduce risks, help save the environment, human health, and even lives. For example, voice, image, and text recognition that is based on ML algorithms enable better compliance to EHS regulations, as it can analyze huge amounts of visual and verbal data, detect errors, as well as alert users to potential hazards.

    Deep Learning is a subsection of ML, which implies artificial neural networks and algorithms that are designed the way the human nervous system is. The technology is able to learn from extremely large amounts of data. By analyzing and categorizing a company’s data, the system can handle waste management and risk assessment, improve occupational safety and health, and enhance operational efficiency.

    Computer Vision for video analytics. Each and every company collects an enormous amount of data with the help of cameras. This data can be analyzed automatically for the determination of a violation of the norms. In case of any problematic situation detection, the supervisor will be notified immediately about this violation.

    Data Mining for Predictive Analytics. By using such techniques as data mining, text mining, reporting modeling, and statistics, predictive analytics can identify potential risks and forecast the most likely outcome. The benefits OF T
    application for the EHS industry are evident: it can control emissions, mitigate risks, identify trends, and perform preventative measures. In other words, AI takes human error out of workplace incidents. 

    As AI is edging its way into our lives, AI tools and techniques are gradually coming into play in the EHS sector, reducing emissions, improving accident rates, enhancing safety, and managing employee health. By applying AI-driven technologies, enterprises can enjoy significant financial and environmental benefits, a greater reputation, and long-term business growth based on sustainable and environmentally sound operations.

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