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.
Locus Technologies founder and CEO Neno Duplan provides a wealth of experience on water quality in the cloud. Neno began cloud-based data work before any of us knew what the cloud even was. He does a great job explaining the steps needed to undertake and the significant benefits of a cloud-based digital transformation, and much more!
A growth in commitment from proactive organizations towards heightened ESG standards means that many professionals have seen their duties not only increase, but they have been made more diverse than before.
Locus EIM is the leading cloud-based application for managing and reporting environmental data. We have highlighted 5 key usability features that allow users to get the most out of their investment.
The recent year of lockdowns pushed many daily activities into the virtual world. Work, school, commerce, the arts, and even medicine have moved online and into the cloud. As a result, considerably more resources and information are now available from an internet browser or from an application on a handheld device. To navigate through all this content and make sense of it, you need the ability to quickly search and get results that are most relevant to your needs.
You can think of the web as a big database in the cloud. Traditionally, database searches were done using a precise syntax with a standard set of keywords and rules, and it can be hard for non-specialists to perform such searches without learning programming languages. Instead, you want to search in as natural a matter as possible. For example, if you want to find pizza shops with 15 miles of your house that offer delivery, you don’t want to write some fancy statement like “return pizza_shop_name where (distance to pizza shop from my house < 15 miles) and (offers_delivery is true). You just want to type “what pizza shops within 15 miles of my house offer delivery?” How can this be done?
Enter the search engine. While online search engines appeared as early as 1990, it wasn’t until Yahoo! Search appeared in 1995 that their usage became widespread. Other engines such as Magellan, Lycos, Infoseek, Ask Jeeves, and Excite soon followed, though not all of them survived. In 1998, Google hit the internet, and it is now the most dominant engine in use. Other popular engines today are Bing, Baidu, and DuckDuckGo.
Current search engines compare your search terms to proprietary indexes of web page and their content. Algorithms are used to determine the most relevant parts of the search terms and how the results are ranked on the page. Your search success depends on what search terms you enter (and what terms you don’t enter). For example, it is better to search on ‘pizza nearby delivery’ than ‘what pizza shops that deliver are near my house’, as the first search uses less terms and thus more effectively narrows the results.
Search engines also support the use of symbols (such as hyphens, colons, quote marks) and commands (such as ‘related’, ‘site’, or ‘link’) that support advanced searches for finding exact word matches, excluding certain results, or limiting your search to certain sites. To expand on the pizza example, support you wanted to search for nearby pizza shops, but you don’t want to include Nogud Pizza Joints because they always put pineapple on your pizza. You would need to enter ‘pizza nearby delivery -nogud’. In some ways, with the need to know special syntax, searching is back where it was in the old database days!
Search engines are also a key part of ‘digital personal assistants’, or programs that not only perform searches but also perform simple tasks. An assistant on your phone might call the closest pizza shop so you can place an order, or perhaps even login to your loyalty app and place the order for you. There is a dizzying array of such assistants used within various devices and applications, and they all seem to have soothing names such as Siri, Alexa, Erica, and Bixby. Many of these assistants support voice activation, which just reinforces the need for natural searches. You don’t want to have to say “pizza nearby delivery minus nogud”! You just want to say “call the nearest pizza shop that does delivery, but don’t call Nogud Pizza”.
Search engine and digital personal assistant developers are working towards supporting such “natural” requests by implementing “natural language processing”. Using natural language processing, you can use full sentences with common words instead of having to remember keywords or symbols. It’s like having a conversation as opposed to doing programming. Natural language is more intuitive and can help users with poor search strategies to have more successful searches.
Furthermore, some engines and assistants have artificial intelligence (AI) built in to help guide the user if the search is not clear or if the results need further refinement. What if the closest pizza shop that does delivery is closed? Or what if a slightly farther pizza place is running a two-for-one special on your favorite pizza? The built-in AI could suggest choices to you based on your search parameters combined with your past pizza purchasing history, which would be available based on your phone call or credit charge history.
The Locus team recently expanded the functionality of the EIM (Environmental Information Management) search bar to support different types of data searches. If a search term fits several search types, all are returned for the user to review.
EIM lets the user perform successful searches through various methods. In all searches, the user does not need to specify if the search term is a menu item, help page, or data entity such as parameter or location. Rather, the search bar determines the most relevant results based on the data currently in EIM. Furthermore, the search bar remembers what users searched for before, and then ranks the results based on that history. If a user always goes to a page of groundwater levels when searching for location ‘MW-1’, then that page will be returned first in the list of results. Also, the EIM search bar supports common synonyms. For example, searches for ‘plot’, ‘chart’, and ‘graph’ all return results for EIM’s charting package.
By implementing the assistance methods described above, Locus is working to make searching as easy as possible. As part of that effort, Locus is working to add natural language processing into EIM searches. The goal is to let users conduct searches such as ‘what wells at my site have benzene exceedances’ or perform tasks such as ‘make a chart of benzene results’ without having to know special commands or query languages.’
How would this be done? Let’s set aside for now the issues of speech recognition – sadly, you won’t be talking to EIM soon! Assume your search query is ‘what is the maximum lead result for well 1A?’
A similar process could be done for tasks such as ‘make a chart of xylene results’. In this case, however, there is too much ambiguity to proceed, so EIM would need to return queries for additional clarifications to help guide the user to the desired result. Should the chart show all dates, or just a certain date range? How are non-detects handled? Which locations should be shown on the chart? What if the database stores separate results for o-Xylene, m,p-Xylene, plus Xylene (total)? Once all questions were answered, EIM could generate a chart and return it to the user.
Natural language is the key to helping users construct effective searches for data, whether in EIM, on a phone, or in the internet. Locus continues to improve EIM by bringing natural language processing to the EIM search engine.
About the Author—Dr. Todd Pierce, Locus Technologies
Dr. Pierce manages a team of programmers tasked with development and implementation of Locus’ EIM application, which lets users manage their environmental data in the cloud using Software-as-a-Service technology. Dr. Pierce is also directly responsible for research and development of Locus’ GIS (geographic information systems) and visualization tools for mapping analytical and subsurface data. Dr. Pierce earned his GIS Professional (GISP) certification in 2010.
Streamline and simplify annual CCR preparation with Locus water quality software—designed for water systems to simplify the sampling, management, and reporting of drinking water data.
Humankind has produced hundreds of millions of tons of plastics since the 1950s. A relatively small proportion of these plastics (less than 10%) has been recycled; some has been incinerated; and a significant amount has been entombed in landfills. A small, but significant proportion of those plastics end up as microplastics (plastic particles less than 5 microns in size). Experts estimate that as many as 1.5 million tons of microplastics are released to surface water (oceans, rivers, lakes) every year. These particles don’t readily break down in the environment—which means they accumulate in the water.
So what does that mean? If even half of the microplastics that entered the waters over the last 10 years are still there, and they are evenly distributed across all the water on Earth, it means that every liter of water on the planet has over 500 tiny pieces of plastic floating around in it.
Of course, the plastic isn’t evenly distributed—we haven’t contaminated the deep oceans to the same extent we’ve contaminated rivers, lakes and other surface waters, from which we draw our drinking water. The World Health Organization (WHO) recently reported that studies of drinking water show it contains up to 1000 particles/L. WHO showed that the two most common plastic particle were PET (polyethylene terephthalate), commonly found in clothing and food containers, and polypropylene (bags, packaging and some fibers).
People don’t know how bad these are. General consensus among experts is it depends on the type of plastics: polyethylene is probably not bad, phthalates are worse, and chlorinated compounds such as vinyl chloride are far worse.
Regulators are starting to take notice: REACH in EU and CA both have proposed regulations for microplastics in drinking water. The REACH regulations attack the problem at the source. They include measurement of microplastics that are shed from clothing and fibers, which are the source of up to 35% of the microplastics in the environment. California will likely start with a preliminary guideline to help water suppliers measure and assess the microplastics in their systems.
As a drinking water supplier, you need to be prepare to manage microplastics. A good first step is having a flexible software system such as Locus, in place to track microplastics. The system should track the sampling and lab methodology as well as the data results, so you can continue not just to track your data, but assess its meaning in the face of evolving regulations and methodologies.
As a consumer of water, begin by cutting down on plastics usage. Wear cotton or other apparel which doesn’t include synthetics.
About the Author—Steve Paff, Locus Technologies
Steve Paff is a Sales Engineer, Product Manager and Implementation specialist with over 25-years’ experience delivering quality software solutions for environmental, health, safety and sustainability. Mr. Paff has extensive experience in many of the industry’s software suites. He came to Locus as Senior Sales Engineer after developing and launching a Covid-19 contact tracing app and developing an app to track sustainability metrics across the global apparel supply chain.
Attention all water providers: the EPA’s UCMR 5 list includes 30 contaminants (29 PFAS and lithium) that both small and large water systems have to test for and report. Can your current environmental solution handle it?
Locus EIM environmental software can handle new chemicals and analyses seamlessly. Both the standard Locus EIM configuration and the Locus EIM Water configuration (specially tailored to water utilities) are built with ever-changing regulations in mind.
We’ve put together some helpful background and tips for water providers preparing for UCMR 5 monitoring.
In 1996, Congress amended the Safe Drinking Water Act with the Unregulated Contaminant Monitoring Rule (UCMR). Under this new rule, US EPA can require water providers to monitor and collect data for contaminants that may be in drinking water but don’t have any health-based standards set (yet) under the SDWA.
More than 150,000 public water systems are subject to the SDWA regulations. US EPA, states, tribes, water systems, and the public all work together to protect the water supply from an ever-growing list of contaminants.
However, under the UCMR, US EPA is restricted to issuing a new list every five years of no more than 30 unregulated contaminants to be monitored by water providers.
This helps reduce the burden on water providers, since monitoring and testing for the existing long list of regulated contaminants already requires a significant investment of time and resources.
Throughout the course of this monitoring, US EPA can determine whether the contaminants need to be officially enforced— but this would require regulatory action, routed through the normal legislative process.
Contact your Locus Account Manager for help setting up your EIM database in advance of your sampling schedule, and we’ll make sure you’re equipped for UCMR 5!
Not yet a customer? Send us a quick note to schedule a call or a demo to find out how Locus software can completely streamline your water sampling and reporting.
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Maybe you are a user of Locus’ Environmental Software (EIM) and are looking to get more out of our product. Or perhaps you are using another company’s software platform and looking to make a switch to Locus’ award-winning solution. Either way, there are some features that you may not know exist, as Locus software is always evolving by adding more functionality for a range of customer needs. Here are five features of our environmental software that you may not know about:
Locus expanded the EIM application programming interface (API) to support running any EIM Expert Query. Using a drag and drop interface, an EIM user can create an Expert Query to construct a custom SQL query that returns data from any EIM data table. The user can then call the Expert Query through the API from a web browser or any application that can consume a REST API. The API returns the results in JSON format for download or use in another program. EIM power users will find the expanded API extremely useful for generating custom data reports and for bringing EIM data into other applications.
The Expert Query Builder lets users schedule their custom queries to run at given times with output provided in an FTP folder or email attachment. Users can view generated files through the scheduler in a log grid, and configure notifications when queries are complete. Users can scheduled queries to run on a daily, weekly, monthly, or yearly basis, or to run after an electronic data deliverable (EDD) of a specified format is loaded to EIM. Best of all, these queries can be instantly ran and configured from the dashboard.
Scheduled Queries in Locus EIM
Multiple charts can be created in EIM at one time. Charts can then be formatted using the Format tab. Formatting can include the ability to add milestone lines and shaded date ranges for specific dates on the x axis. The user can also change font, legend location, line colors, marker sizes and types, date formats, legend text, axis labels, grid line intervals or background colors. In addition, users can choose to display lab qualifiers next to non-detects, show non-detects as white filled points, show results next to data points, add footnotes, change the y-axis to log scale, and more. All of the format options can be saved as a chart style set and applied to sets of charts when they are created.
Chart Formatting in Locus EIM
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.
Locus EIM Quick Search
When the user runs the template for a specific set of locations, EIM displays the callouts in Locus’ premium GIS software, 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
The DMR tool in Locus’ Environmental Information Management (EIM) software solves the problem of time-consuming, labor-intensive, and expensive manual report generation by automating the data assembly, calculations, and formatting of Discharge Monitoring Reports. Depending on the type of discharge and the regulatory jurisdiction, you may be required to report information such as analytical chemistry of pollutants, flow velocity, total maximum daily load, and other parameters. For companies that report on multiple facilities, producing a DMR also becomes a major expense.
Thanks to Locus’ DMR tool, companies can generate DMRs within minutes with validated data in approved formats, with all of the calculations completed according to regulatory requirements. Companies can set up EIM for its permitted facilities and realize immediate cost and time savings during each reporting period. Locus users have saved over $2,000,000 on DMR reporting.
Locus continues to enhance the Discharge Monitoring Report (DMR) tool, recently implementing calculations needed to handle reporting of divalent metals. New formats, such as Florida DEP ezDMR, are regularly being added, so customers can meet their reporting requirements.