Tag Archive for: IoT

Locus provides multiple methods to populate EHS, ESG, or any environmental data, including the following:

6 Ways to Input Data

 

Integrations

Locus provides a full suite of REST API’s, and SDK that can be used to populate data from external data sources. Typical uses include utility data, CEMS, meter data and IoT data.

 

Surveys

Locus Survey tool enables you to issue survey questionnaires to people outside your organization, and enables them to securely and seamlessly respond directly into the survey form. Typical uses include supplier surveys, audits and customer questionnaires.

 

Mobile

User input forms can be optimized for input on a phone or tablet, which allows quick uploads of photos and also geotags your data so you can ensure it was collected at the right location.

 

Excel and Text Files

Locus provides a full suite of Excel upload tools that allow you to import data directly from Excel or CSV files. This option also allows you to work offline and re-sync your data later. Typical uses include laboratory data, periodic monitoring data and data migrations.

 

Manual Data

Like any system, Locus provides tools for users to directly enter data into the system. These include Locus sophisticated data validation tools which employs machine learning techniques to identify data entries which may be invalid, with visual indications of the expect range or ranges.

 

Email

Locus can be configured to directly read email input (as text) and place it into the system. Typical uses include instances where external users initiate a conversation, which then may be responded to from within the system, such as an inquiry, issue, or an incident report.

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Send us your contact information and a Locus representative will be in touch to discuss your organization’s environmental data management needs and provide an estimate, or set up a free demo of our enterprise environmental software solutions.

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    Locus Founder and CEO, Neno Duplan recently sat down with Grant Ferrier of 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.

    [icoLocus name=”list”]  Use the video chapters to navigate to areas of interest.

    Neno Duplan is founder and CEO of Locus Technologies, a Silicon Valley-based environmental software company founded in 1997. Locus evolved from his work as a research associate at Carnegie Mellon in the 1980s, where he developed the first prototype system for environmental information management. This early work led to the development of numerous databases at some of the nation’s largest environmental sites, and ultimately, to the formation of Locus in 1997.

    Click here to learn more and purchase the full EBJ Vol XXXIII No 5&6: Environmental Industry Outlook 2020-2021

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    Let’s look back on the most exciting new features and changes made in EIM, Locus’ environmental data management software, during 2019!

    1. Migration to AWS Cloud

    In August, Locus migrated EIM into the Amazon Web Services (AWS) cloud. EIM already had superior security, reliability, and performance in the Locus Cloud. The move to AWS improves on those metrics and allows Locus to leverage AWS specific tools that handle big data, blockchain, machine learning, and data analytics. Furthermore, AWS is scalable, which means EIM can better handle demand during peak usage periods. The move to AWS helps ensure that EIM remains the world’s leading water quality management software.

    Infographic: 6 Benefits of EHS on AWS

    2. SSO Login

    EIM now supports Single Sign-On (SSO), allowing users to access EIM using their corporate authentication provider. SSO is a popular security mechanism for many corporations. With SSO, one single login allows access to multiple applications, which simplifies username and password management and reduces the number of potential targets for malicious hacking of user credentials. Using SSO with EIM requires a one-time configuration to allow EIM to communicate with a customer’s SSO provider.

    Locus Single Sign On (SSO)

    3. GIS+ Data Callouts

    The Locus GIS+ solution now supports creating data callouts, which are location-specific crosstab reports listing analytical, groundwater, or field readings. A user first creates a data callout template using a drag-and-drop interface in the EIM enhanced formatted reports module. The template can include rules to control data formatting (for example, action limit exceedances can be shown in red text). When the user runs the template for a specific set of locations, EIM displays the callouts in the GIS+ as a set of draggable boxes. The user can finalize the callouts in the GIS+ print view and then send the resulting map to a printer or export the map to a PDF file.

    Locus GIS+ Data Callouts

    4. EIM One

    For customers who don’t require the full EIM package, Locus now offers EIM One, which gives the ability to customize EIM functionality. Every EIM One purchase comes with EIM core features: locations and samples; analytical and field results; EDD loading; basic data views; and action limit exceedance reports. The customer can then purchase add-on packages to get just the functionality desired–for example a customer with DMR requirements may purchase the Subsurface and Regulatory Reporting packages. EIM One provides customers with a range of pricing options to get the perfect fit for their data management needs.

    EIM One Packages

    5. IoT data support

    EIM can now be configured to accept data from IoT (internet of things) streaming devices. Locus must do a one-time connection between EIM and the customer’s IoT streaming application; the customer can then use EIM to define the devices and data fields to capture. EIM can accept data from multiple devices every second. Once the data values are in EIM, they can be exported using the Expert Query tool. From there, values can be shown on the GIS+ map if desired. The GIS+ Time Slider automation feature has also been updated to handle IoT data by allowing the time slider to use hours, minutes, and seconds as the time intervals.

    Locus IoT Data

    6. CIWQS and NCDEQ exports

    EIM currently supports several dozen regulatory agency export formats. In 2019, Locus added two more exports for CIWQS (California Integrated Water Quality System Project) and the NCDEQ (North Carolina Department of Environmental Quality). Locus continues to add more formats so customers can meet their reporting requirements.

    CIWQS and NCDEQ Exports

    7. Improved Water Utility reporting

    EIM is the world’s leading water quality management software, and has been used since 1999 by many Fortune 500 companies, water utilities, and the US Government. Locus added two key reports to EIM for Water in 2019 to further support water quality reporting. The first new report returns chlorine averages, ranges, and counts. The second new report supports the US EPA’s Lead and Copper rule and includes a charting option. Locus will continue to enhance EIM for Water by releasing the 2019 updates for the Consumer Confidence Report in January 2020.

    Locus Water Utility Reporting

    8. Improved Non-Analytical Views

    Locus continues to upgrade and improve the EIM user interface and user experience. The most noticeable change in 2019 was the overhaul of the Non-analytical Views pages in EIM, which support data exports for locations, samples, field readings, groundwater levels, and subsurface information. Roughly 25 separate pages were combined into one page that supports all these data views. Users are directed through a series of filter selections that culminate in a grid of results. The new page improves usability and provides one centralized place for these data reports. Locus plans to upgrade the Analytical Views in the same way in 2020.

    Non-analytical views in Locus EIM

    9. EIM search box

    To help customers find the correct EIM menu function, Locus added a search box at the top right of EIM. The search box returns any menu items that match the user’s entered search term. In 2020, Locus will expand this search box to return matching help file documents and EDD error help, as well as searches for synonyms of menu items.

    Locus EIM Quick Search

    10. Historical data reporting in EDD loading

    The EIM EDD loader now has a new “View history” option for viewing previously loaded data for the locations and parameters in the EDD. This function lets users put data in the EDD holding table into proper historical context. Users can check for any unexpected increases in parameter concentrations as well as new maximum values for a given location and parameter.

    Historical Data in Locus EIM

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      More recently, big data has become more closely tied to IoT-generated streaming datasets such as Continued Air Emission Measurements (CEMS), real-time remote control and monitoring of treatment systems, water quality monitoring instrumentation, wireless sensors, and other types of wearable mobile devices. Add digitized historical records to this data streaming, and you end up with a deluge of data. (To learn more about big data and IoT trends in the EHS industry, please read this article: Keeping the Pulse on the Planet using Big Data.) 

      In the 1989 Hazardous Data Explosionarticle that I mentioned earlier, we first identified the limitation of relational database technology in interpreting data and the importance that IoT (automation as it was called at the time) and AI were going to play in the EHS industry. We wrote: 

      “It seems unavoidable that new or improved automated data processing techniques will be needed as the hazardous waste industry evolves. Automation (read IoT) can provide tools that help shorten the time it takes to obtain specific test results, extract the most significant findings, produce reports and display information graphically,” 

      IoT - Internet of Things

      We also claimed that “expert systems” (a piece of software programmed using artificial intelligence (AI) techniques. Such systems use databases of expert knowledge to offer advice or make decisions.) and AI could be possible solutions—technologies that have been a long time coming but still have a promising future in the context of big data. 

      “Currently used in other technical fields, expert systems employ methods of artificial intelligence for interpreting and processing large bodies of information.” 

      Although “expert systems” as a backbone for AI did not materialize as it was originally envisioned by researches, it was a necessary step that was needed to use big data to fulfil the purpose of an “expert”. 

      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 application include AI-infused permit management, AI-based permit interpretation and response to regulatory agencies, precision sampling, predicting natural attenuation of chemicals in water, managing sustainable supply chains, automating environmental monitoring and enforcement, and enhanced sampling and analysis based on real-time weather forecasts. 

      Parts one, three, and four of this blog series complete the overview of Big Data, IoT, AI and multi-tenancy. We look forward to feedback on our ideas and are interested in hearing where others see the future of AI in EHS software – contact us for more discussion or ideas!

      Contact us to learn more about Locus uses IoT and AI

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        On 12 April 2019, Locus’ Founder and CEO, Neno Duplan, received the prestigious Carnegie Mellon 2019 CEE (Civil and Environmental Engineering) Distinguished Alumni Award for outstanding accomplishments at Locus Technologies. In light of this recognition, Locus decided to dig into our blog vault, share a series of visionary blogs crafted by our Founder in 2016. These ideas are as timely and relevant today as they were three years ago, and hearken to his formative years at Carnegie Mellon, which formed the foundation for the current success of Locus Technologies as top innovator in the water and EHS compliance space.

        Artificial Intelligence (AI) for Better EHS Compliance (original blog from 2016)

        It is funny how a single acronym can take you back in time. A few weeks ago when I watched 60 Minutes’ segment on AI (Artificial Intelligence) research conducted at Carnegie Mellon University, I was taken back to the time when I was a graduate student at CMU and a member of the AI research team for geotechnical engineering. Readers who missed this program on October 9, 2016, can access it online.

        Fast forward thirty plus years and AI is finally ready for prime time television and a prominent place among the disruptive technologies that have so shaken our businesses and society. This 60 Minutes story prompted me to review the progress that has occurred in the field of AI technology, why it took so long to come to fruition, and the likely impact it will have in my field of environmental and sustainability management. I discuss these topics below. I also describe the steps that we at Locus have taken to put our customers in the position to capitalize on this exciting (but not that new) technology.

        What I could not have predicted when I was at Carnegie Mellon is that AI was going to take a long time to mature–almost the full span of one’s professional career. The reasons for this are multiple, the main one being that several other technologies were absent or needed to mature before the promises of AI could be realized. These are now in place. Before I dive into AI and its potential impact on the EHS space, let me touch on these “other” major (disruptive) technologies without which AI would not be possible today: SaaS, Big Data, and IoT (Internet of Things).

        Locus Artificial Intelligence

        As standalone technologies, each of these has brought about profound changes in both the corporate and consumer worlds. However, these impacts are small when compared to the impact all three of these will have when combined and interwoven with AI in the years to come. We are only in the earliest stages of the AI computing revolution that has been so long in the coming.

        I have written extensively about SaaS, Big Data, and IoT over the last several decades. All these technologies have been an integral part of Locus’ SaaS offering for many years now, and they have proven their usefulness by rewarding Locus with contracts from major Fortune 500 companies and the US government. Let me quickly review these before I dive into AI (as AI without them is not a commercially viable technology).


        Big Data

        Massive quantities of new information from monitoring devices, sensors, treatment systems controls and monitoring, and customer legacy databases are now pouring into companies EHS departments with few tools to analyze them on arrival. Some of the data is old information that is newly digitized, such as analytical chemistry records, but other information like streaming of monitoring wireless and wired sensor data is entirely new. At this point, most of these data streams are highly balkanized as most companies lack a single system of record to accommodate them. However, that is all about to change.

        As a graduate student at Carnegie Mellon in the early eighties, I was involved with the exciting R&D project of architecting and building the first AI-based Expert System for subsurface site characterization, not an easy task even by today’s standards and technology. AI technology at the time was in its infancy, but we were able to build a prototype system for geotechnical site characterization, to provide advice on data interpretation and on inferring depositional geometry and engineering properties of subsurface geology with a limited amount of data points. The other components of the research included a relational database to store the site data, graphics to produce “alternative stratigraphic images” and network workstations to carry out the numerical and algorithmic processing. All of this transpired before the onset of the internet revolution and before any acronyms like SaaS, AI, or IoT had entered our vocabulary. This early research led to the development of a set of commercial tools and technological improvements and ultimately to the formation of Locus Technologies in 1997.

        Part of this early research included management of big data, which is necessary for any AI undertaking. As a continuation of this work at Carnegie Mellon, Dr. Greg Buckle and I published an article in 1989 about the challenges of managing massive amounts of data generated from testing and long-term monitoring of environmental projects. This was at a time when spreadsheets and paper documents were king, and relational databases were little used for storing environmental data.

        The article, “Hazardous Data Explosion,“ published in the December 1989 issue of the ASCE Civil Engineering Magazine, was among the first of its kind to discuss the upcoming Big Data boom within the environmental space and placed us securely at the forefront of the big data craze. This article was followed by a sequel article in the same magazine in 1992, titled “Taming Environmental Data,“ that described the first prototype solution to managing environmental data using relational database technology. In the intervening years, this prototype eventually became the basis of the industry’s first multi-tenant SaaS system for environmental information management.

        Locus - Big Data - IoT - AI

        Today, the term big data has become a staple across various industries to describe the enormity and complexity of datasets that need to be captured, stored, analyzed, visualized, and reported. Although the concept may have gained public popularity relatively recently, big data has been a formidable fixture in the EHS industry for decades. Initially, big data in EHS space was almost entirely associated with the results of analytical, geotechnical, and field testing of water, groundwater, soil, and air samples in the field and laboratory. Locus’ launch of its Internet-based Environmental Information Management (EIM) system in 1999 was intended to provide companies not only with a repository to store such data, but also with the means to upload such data into the cloud and the tools to analyze, organize, and report on these data.

        In the future, companies that wish to remain competitive will have no choice but bring together their streams of (seemingly) unrelated and often siloed big data into systems such as EIM that allow them to evaluate and assess their environmental data with advanced analytics capabilities. Big data coupled with intelligent databases can offer real-time feedback for EHS compliance managers who can better track and offset company risks. Without the big data revolution, there would be no coming AI revolution.


        AI and Water Management – Looking Ahead

        There has been much talk about how artificial intelligence (AI) will affect various aspects of our lives, but little has been said to date about how the technology can help to make water quality management better. The recent growth in AI spells a big opportunity for water quality management. There is enormous potential for AI to be an essential tool for water management and decoupling water and climate change issues.

        Two disruptive megatrends of digital transformation and decarbonization of economy could come together in the future. AI could make a significant dent in global greenhouse gas (GHG) emissions by merely providing better tools to manage water. The vast majority of energy consumption is wasted on water treatment and movement. AI can help optimize both.

        AI is a collective term for technologies that can sense their environment, think, learn, and take action in response to what they’re detecting and their objectives. Applications can range from automation of routine tasks like sampling and analyses of water samples to augmenting human decision-making and beyond to automation of water treatment systems and discovery – vast amounts of data to spot, and act on patterns, which are beyond our current capabilities.

        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.

        Parts two, three, and four of this blog series complete the overview of Big Data, Iot, AI and multi-tenancy. We look forward to feedback on our ideas and are interested in hearing where others see the future of AI in EHS software – contact us for more discussion or ideas!

        Contact us to learn more about Locus uses IoT and AI

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          IoT is considered one of the fastest growing trends in technology and has a potentially huge impact to automate how we manage water quality, air emissions and other key environmental performance indicators for data monitoring.

          In the following webinar, we focused on how various industries can benefit from integration and interoperability of a multi-tenant cloud platform and Internet of Things (IoT) platforms for managing, organizing and monitoring the structured and unstructured data coming from various different sources. Once in the platform, a centralized data repository is created that is suitable for analyzing the key environmental indicators for management, sustainability and environmental compliance.

           

           

          With the deployment of IoT through several automated technologies like sensors, programmable logic controllers (PLCs) and other internet and mobile connected devices and other instruments, a masses of real time data is generated that not only needs to be stored but analyzed and managed at interception along with several other sources of structured and unstructured data from different sources. All this data generated by different streaming devices need to be connected through a central place in a scalable cloud-based application to manage compliance and help in real time monitoring of data to come up with for effective solutions for a smarter environment management and sustainability initiatives.

          Internet of Things - IoT

          IoT technology for environmental monitoring is a booming industry.  The IoT growth for the water industry alone is forecasted to be  $20.10 billion by 2021 that indicates the massive volumes of data will be generated that will need to be to be monitored, managed and analyzed in intelligent, well designed software systems. Excel spreadsheets and ad hoc in-house data systems will not be up to the challenge.

          What is the core business problem challenge this webinar will help the audience to solve?

          IoT - Internet of ThingsMany companies are concerned that the sheer volume of data will render the information useless, unless all sources of data mentioned above can be turned into actionable information. This challenge can be addressed via the deployment of a highly scalable, end-user configurable, SaaS-based multi-tenant cloud infrastructure, coupled with environmental data management and compliance software applications.  This configuration can connect all the incoming data and create a central data repository that is easily accessible and available for use with responsive data analytics.

          A multi-tenant SaaS application can help to process the flow of information in an efficient and effective manner, providing better business and information analysis and interpretation by using various integrated tools. Such applications can help in real time monitoring and provide timely alerts for management and compliance.

          Coupled with business analytics, the masses of data can be turned into concise and meaningful information for system users. This approach will solve the problem of managing too much information coming into the organization, and allow it to turn the streaming data into intelligent information to support desired decision-making.

          What are the top takeaways attendees can expect to learn?

          • Learn how to create a single centrally accessible system for recording data from various data monitoring sources.
          • Learn how integrating IoT technologies and a multi-tenant SaaS cloud application can allow companies to switch from periodic monitoring on a prescribed schedule to continuous real-time monitoring, without increasing monitoring cost and thereby reducing operational costs.
          • Learn how to reduce compliance cycle time and benefit from smarter management solutions.
          • Leverage the benefits of cloud computing using real-time tools like GIS applications and rich business analytics for reporting and analysis, timely alerts, etc.

           

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          Blockchain is a highly disruptive technology that promises to change the world as we know it, much like the World Wide Web’s impact after its introduction in 1991. As companies look to the blockchain model to perform financial transactions, trade stocks, and create open market spaces, many other industries are looking at utilizing blockchain technology to eliminate the middleman. One sector well-positioned to benefit from blockchain technology is the data-intensive Environment, Health, Safety and Sustainability (EHS&S) space.

          In particular, I see three major ways that the EHS industry can utilize blockchain technology to change how they manage information: 1) Blockchain-based IoT monitoring, 2) emissions management, and 3) emissions trading.

          My belief is that blockchain technology will help to quantify the impact of man-made emissions on global warming trends and provide tools to manage it. One cannot manage what one cannot measure!

          Imagine this: every emissions source in your company, whether to water, air, or soil, is connected wirelessly via a sensor or another device (thing) to a blockchain ledger that stores a description of the source, its location, emission factors, etc. Every time that the source generates emissions (that is, it is on), all necessary parameters are recorded in real time. If air emissions are involved, equivalent tons of carbon are calculated and recorded in a blockchain ledger and made available to reporting and trading entities in real time.

          Blockchain ledgers may exist at many levels. Some may record emissions at a given site. Others at higher levels (company, state or province, country, continent, etc.) may roll up information from lower level ledgers.

          Suppose that emissions are traded so that they are not yours anymore. In that case, someone else owns them, and you do not need to report them again, but everyone knows that you were the generating source. The same logic can be applied to tier 1, 2, and 3 level emissions. Attached to the emissions ledger are all other necessary information about the asset generating those emissions, financial information, depreciation schedule, time in service, operating time, fuel consumption, operators’ names, an estimate of future emissions—the list goes on.

          To learn more how blockchain technology will impact emissions monitoring, management, reporting, and trading click here.

          Tag Archive for: IoT

          Environmental Business Journal (EBJ) recognized the firm for growth and innovation in the field of Information Technology

          MOUNTAIN VIEW, Calif., 10 February 2020

          Locus Technologies, leading provider of environmental management and EHS software, was awarded a 14th consecutive award from Environmental Business Journal (EBJ) for growth and innovation in the field of Information Technology.

          EBJ is a business research publication providing strategic business intelligence to the environmental industry. Locus received the 2019 EBJ Award for Information Technology by expanding their software and services.

          Among the key drivers for Locus in 2019 was the growth of key software applications for waste and sustainability, as well as the introduction of their facilities management app. Locus software also now further integrates with EPA compliance systems like CMDP, eManifest, and eGGRT. Finally, in terms of services, Locus achieved over 500 GHG verifications under the California AB32 program, being the first company to do so. They were also among the first independent bodies to become certified for the new California Low Carbon Fuel Standard verification.

          “We would like to express our gratitude for receiving the EBJ Information Technology award for another year. We look forward to providing our customers with cutting-edge software and services as we seek to improve in the areas of artificial intelligence, IoT integration, and blockchain technology,” said Wes Hawthorne, President of Locus Technologies.