Incident / Accident Management is requirement for many guidelines and regulations and needed to be properly managed within an organization. If an incident is not properly managed it results in loss of information, chances for incident avoidance in future and monetary challenges. Deep Learning Techniques like Tensorflow / Keras along with OpenCV and other libraries can be used to automatically manage incidents / accidents within an organization.
Safety Data Sheet suppliers are usually required to provide emergency telephone number in section 1 of the SDSs. Some regulations even recommend having 24/7 local emergency telephone numbers. OSHA clearly states that the telephone number should be provided for person / entity who is either knowledgeable of the hazardous material being shipped and who has comprehensive emergency response and incident mitigation information for that material. However, companies are facing issues with availability of knowledgeable persons / staff who can be available for 24/7 to carry out such tasks.
Dangerous Goods classification is one of the critical activities for any organization to maintain compliance with regulatory requirements and also ensuring not to harm persons and environment. The classification of Dangerous goods is a skill which is getting scarce in organizations due to various reasons like availability of SME’s and knowledge gaps etc.
It started some two years back when I started exploring Data Science (Python, R, Azure ML & Knime) to understand the new possibilities for EHS, which I slowly expanded by refreshing my IoT skills, Big Data (Hortonworks / HDInsight) & Cloud skills (AWS & Azure) and Blockchain skills. Then I started exploring various Digital Transformation books like The Digital Transformation Play book by David L Rogers and Leading Digital by HBR. After spending some two years on this topic today I am finally publishing a Not A very short video on "Digital Transformation of EHS".
Recently a friend of mine told me that their organization is embarking on to the journey of digital transformation. I said wow, what exactly it is doing for which his response was that their implementation of portal system for logging records. Does it quality to be called a digital transformation ? is it so ?
Sometime back I wrote a blog on Use of AI / ML for managing Incident Management, it has received good response. I have received many requests to know in detail on how to implement the same and details surrounding it and some even requested me to share the source code. In this current blog and series of upcoming blogs I would like to share some short course on Introduction to Data Science and how it is used for managing the EHS issues. There are many relevant issues which can be solved using AI / ML, be it Descriptive Statistics, Predictive Analysis of incidents / exceptions for air permits or equipment based pollution deviations or even customer / supplier perception of the risks around the products being sold by the organization, automatic classification of dangerous goods based on past history, prediction of product compliance based on source and many more proprietary uses.
There has been some changes happening in the field of SAP EHS being it introduction of S/4HANA; S/4HANA Cloud based EHS solutions. Be it Business Suite applications or Product Compliance suite for S/4HANA Cloud, it is changing the way the EHS is working till now. In this short video I tried to give an overview on different EHS business processes covering all modules of EHS which have been introduced till date excepting for modules like SAP Carbon Impact 4.0 or Tools like Document Analyzer, Web based MSDS hosing, SAP Product and REACH compliance, CfP, Data Editor etc.
I have involved in couple of assessments over the adaptation of Robotic Process Automation for meeting Regulatory Compliance. It was a detailed analysis of existing processes for the RPA potential. I would like to share the some of the experience from the exercise.
As you must have noticed that Development of Machine Learning / AI projects largely aligned to specific groups inside the organization. Those who have specialized skills handle the development, testing and operationalization of the components.
Some two decades back when my sister, Meera was working for her Doctoral Thesis titled “ Gene Identification and Extraction for Salt Stress in Paddy Plants”, I was super excited with the topic as I knew salt stress tolerant species will help a lot to farmers.
For the past many days my wife has been complaining that her sacred plant (Tulasi – Scientific Name – Ocimum sanctum) is getting dried up due to intense heat. Thanks to urban heating effect. She tried many ways of managing the plant but her busy schedule always hinder in getting real time view of the moisture level and other conditions. I was teased to find a solution to resolve this given that I spend time with IoT and Data Science or Big Data jargons. I tried a variety of tools starting with Moisture sensors, NoIR for NDVI calculation to TensorFlow based image classification to come of with solution.
On Day to day basis farmers needs weather insights as well as storage conditions at various storage units. They need real time insights on different agriculture related information. One of the options is for a tailored virtual assistants which can interact with users and internet sites on a regular basis giving insights.