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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".

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.

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.

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