Why a Metadata-Driven EHS and ESG Platform is the Future of Scalable Business Process Innovation for Large Corporations
Locus Platform and its ecosystem of EHS and ESG software is built to be agile and built on a metadata-driven platform.
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Locus Platform and its ecosystem of EHS and ESG software is built to be agile and built on a metadata-driven platform.
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Locus Technologies continues to explore new frontiers such as a “natural language” AI chatbot for data stored in Locus software.
There are two promising technologies that are about to change how we aggregate and manage EHS+S data: artificial intelligence (AI) and blockchain. When it comes to technology, history has consistently shown that the cost will always decrease, and its impact will increase over time. We still lack access to enough global information to allow AI to make a significant dent in global greenhouse gas (GHG) emissions by merely providing better tools for emissions management. For example, the vast majority of energy consumption is wasted on water treatment and movement. AI can help optimize both. Along the way, water quality management becomes an add-on app.
AI is a collective term for technologies that can sense their environment, think, learn, and act in response to what they’re detecting and their objectives. Possible applications include (1) Automation of routine tasks like sampling and analyses of water samples, (2) Segregation of waste disposal streams based on the waste containers content, (3) Augmentation of human decision-making, and (4) Automation of water treatment systems. AI systems can greatly aid the process of discovery – processing and analyzing vast amounts of data for the purposes of spotting and acting on patterns, skills that are difficult for humans to match. AI can be harnessed in a wide range of EHS compliance activities and situations to contribute to managing environmental impacts and climate change. Some examples of applications include permit interpretation and response to regulatory agencies, precision sampling, predicting natural attenuation of chemicals in water or air, managing sustainable supply chains, automating environmental monitoring and enforcement, and enhanced sampling and analysis based on real-time weather forecasts. Applying AI in water resource prediction, management, and monitoring can help to ameliorate the global water crisis by reducing or eliminating waste, as well as lowering costs and lessening environmental impacts. A similar analogy holds for air emissions management.
The onset of blockchain technology will have an even bigger impact. It will first liberate data and, second, it will decentralize monitoring while simultaneously centralizing emissions management. It may sound contradictory, but we need to decentralize in order to centralize management and aggregate relevant data across corporations and governmental organizations without jeopardizing anyone’s privacy. That is the power of blockchain technology. Blockchain technology will eliminate the need for costly synchronization among stakeholders: corporations, regulators, consultants, labs, and the public. What we need is secure and easy access to any data with infinite scalability. It is inevitable that blockchain technology will become more accessible with reduced infrastructure over the next few decades. My use of reduced architecture here refers to a replacement of massive centralized databases controlled by one of the big four internet companies using the hub-and-spoke model concept with a device-to-device communication with no intermediaries.
This post was originally published in Environmental Business Journal in June of 2020.
Locus Founder and CEO, Neno Duplan recently sat down with Grant Ferrier of the Environmental Business International to discuss a myriad of topics relating to technology in the environmental industry such as Artificial Intelligence, Blockchain, Multi-tenancy, IoT, and much more.
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Locus Technologies provides cloud-based environmental software and mobile solutions for EHS, sustainability management, GHG reporting, water quality management, risk management, and analytical, geologic, and ecologic environmental data management.