Latest Contributions by TomDeWitte

Staying Safe When it Really Matters By Tom Coolidge and Tom DeWitte On rare occasions natural gas from a leaking pipe accumulates inside a building. Gas-filled buildings are known as “Gas-Filled Occupancies” or GFOs for short. GFOs pose an obviously high level of risk due to the potential of an explosion if the accumulation ignites. The question needing answered by first responders and all in proximity to the building is just how far away from a GFO do they need to be to be safe? And the natural follow-on question is how can first responders best be aware of that answer during their emergency activity? In terms of existing industry practice, there is no one industry-standard answer to those questions. Each gas utility determines its own policy and practice based on its own unique circumstances and environment. Callers reporting an odor of gas sometimes are told to move outside at least 330 feet away, while others are told to move some other given distance based upon the gas utility’s own criteria or to an unspecified “safe location.” Gas utilities now can better answer those questions for themselves thanks to an initiative of the American Gas Association (AGA). The AGA’s Gas-Filled Occupancy Task Force that was initiated by the AGA Safety and Occupational Health Committee evaluated a decade of GFO explosions to examine the risk relationship between the GFO explosion location and the location of resulting fatalities or injuries. The criticality of GIS as a tool for first responders and all involved in GFO incidents jumped off the pages to me as I read the Task Force’s recent “Gas-Filled Occupancies – Emergency Response” technical paper. Reading the AGA paper also reminded me of one of my favorite IMGIS 2021 Conference presentations that focused on the use of GIS in GFO response situations. The research done by the Task Force found that there were 78 fatalities and approximately 350 reported injuries as a result of a GFO explosion between 2010 and 2020. Not surprisingly, in general, the further a person is away from a GFO explosion, the safer they are. It was concluded that utility worker and fire department fatalities typically occurred within 50 to 100 ft of structure. Most injuries related to a GFO explosion typically were within 100 to 200 ft of the structure and could be characterized as typically minor. If you haven’t already, I strongly encourage you to read the Task Force technical paper. It is really good work on a topic of obvious importance! The AGA Task Force work is specific to GFOs. Among previous guidance referenced by gas utilities is another that is more general. That reference is found in the U. S. Department of Transportation Emergency Response Guidebook. The guidebook specifies there should be a 100-meter (330 feet) evacuation distance from a natural gas leak in an open area. Given the Task Force’s findings, one approach we expect to see more of is the designation of different zones based on specified distances from a building. The zone closest to the GFO being the highest risk zone, the one furthest away the lowest. This is where a modern GIS can play a significant role. GIS can present all responders and those supporting them with a common operating picture indicating both levels of risk within a certain distance of a building and the location of pipe network components that can isolate the area to make the building – and them - safe. An early example of this approach was highlighted at Esri’s 2021 IMGIS Conference in a presentation titled “How close is too Close?” by Lindsay Dreckman of the Metropolitan Utilities District of Omaha, Nebraska (M.U.D.). Based on the work done by the Task Force, M.U.D. knew the distances from GFO incidents where most fatalities and injuries occurred. M.U.D.’s goal number one was to create a tool to generate three safety zones. Looking at the M.U.D. GFO emergency response policy, those zones include Exclusion, Hazardous, and Risk-Reduction. The Exclusion Zone is from the building’s exterior wall to 100 ft and where zero of our personnel are permitted to access. From 100-200ft is the Hazardous Zone, where work can occur but only after coordination with the public safety incident command. And from 200-330ft is the Risk-Reduction Zone, where we can establish a command post but with protection from a potential explosion. It is important to remember that this is an emergency event. Field crews and first responders need both an immediate visual aid and an automated warning to inform them of these safety zones. A mobile application with an interactive map, such as ArcGIS Field Maps is ideal for this need.  Here is an example highlighting that capability. When this mobile application is loaded onto the field technicians’ phone, or tablet, they will have a mobile device that informs them of these risks. This is possible because today’s mobile devices are location aware. The map can display their location with imagery of the area and the safety zones overlayed. Recent enhancements to ArcGIS Field Maps now enable client side notifications based on that mobile device location awareness.  This is called geofencing.  With geofencing the same field technician can have their mobile device vibrate, make sounds and have a banner notification appear on the mobile device when they approach the safety zones. This client side notification is unique because it works regardless of the phone connection to the network. All in all, it turns out that the AGA Task Force now gives gas utilities an extremely valuable reference to inform their decision-making on GFO response policies and practices. And, not surprisingly, location is key. That puts GIS at the heart of improving safety in a fast-evolving and understandably hectic time of emergency response. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

Automation with Lookup Tables Part 3 0f 5 By Tom DeWitte and Tom Coolidge Our first blog of this series provided an overview of the steps a utility can take to improve the productivity of the utility field worker. If you missed it, you can access it here. The second blog of this series explained how barcodes can help to automate field data collection. If you missed it, you can access it here. In this blog article, we will dig into the second method in automating field data collection. The second method for making life easier for the utility field worker is to deploy a configuration of ArcGIS Field Maps that uses lookup tables to auto-populate what the organization already knows about the asset or data collection activity. As noted in the first blog article, this is the second of four methods to automate field data collection. Minimize manual data entry Auto-populate what is already known Leverage sensors on your mobile device Use geography Solving the Steel Issue Within pipe utility organizations, automating the documentation of steel pipe construction has been a challenge. Unlike plastic pipe, valves, and fittings, there is no industry adopted barcoding standard for steel.  The polyethylene pipe and component manufacturers have adopted the ASTM F2897 barcode standard. But steel has not done so. For many pipe utility organizations, documenting steel pipe construction is a very manual process. It requires the utility field worker to: Obtain the manufacturer paperwork or a copy of manufacturer paperwork to acquire the information about the steel components. Read through the many pages of documentation to find the desired information. Manually enter the retrieved information into the mobile application. Now leave the truck, walk to the construction trench, or direct bore and capture GNSS coordinates of steel components. Return to the truck to retrieve the information for the next unique steel component. Repeat process for each unique steel pipe, steel valve, and steel fitting. Automating the documentation of steel construction requires a different method to streamline data entry. Lookup tables can be that method. What are Lookup Tables Lookup tables are Esri geodatabase tables. The purpose of these tables is to store information that the organization already knows about the specifications of the pipe segment or pipe component prior to construction. In the design and cost estimation phase of a project, this information is often referred to as compatible units. To avoid complications with using these geodatabase tables to auto-populate an asset’s record, the lookup table should be a schema duplicate of the featureclass it is supporting. For example, there should be a separate asset catalog table for just the pipe data.  This geodatabase table would be a schema duplicate of the PipelineLine featureclass in the gas and pipeline industry data model, UPDM.                 Pipe Asset Catalog – PipelineLine schema                 Device Asset Catalog – PipelineDevice schema                 Fitting Asset Catalog – PipelineJunction schema   Auto-Populating what is known When addressing the steel construction documentation issue, these lookup tables contain the information the pipe utility organization knows about the steel pipe or component prior to construction. This is typically more information than is provided by the plastic barcodes. For steel this includes knowing the additional pipe characteristics for Barlow’s equation, such as Specified Minimum Yield Strength (SMYS), outside diameter and design factors. These tables can also contain other steel pipe or component characteristics, such as coating type, and pipe specification. These asset catalog tables are pre-populated with the known information. This pre-population occurs prior to the project entering the construction phase. At many gas and pipeline organizations, this list does not change dramatically between projects. Gas and pipeline organizations have codes and standards that they follow, and a select number of vendors from whom they purchase pipe and pipe components. Deploying the Automation Deploying a technology which is continually, and aggressively enhancing its capabilities, such as ArcGIS, means that sometimes there are different deployment patterns for ArcGIS Field Maps with a certain version of ArcGIS Enterprise versus ArcGIS Field Maps with ArcGIS Online. For ArcGIS Enterprise 10.9.1, the ability to use form calculations in Field Maps did not exist when Enterprise was released in December of 2021. For this environment you will need to use geodatabase attribute rules for the automation.  For this article we will focus on the use of ArcGIS Field Map form calculations, as that provides a consistent capability for an ArcGIS Online deployment and an ArcGIS Enterprise version 11.0 deployment. A key benefit of using ArcGIS Field Map form calculations is that they work in both a connected and disconnected network environment. Step 1: Create asset catalog tables. When duplicating the schema of your system of record layers, it is useful to use the Featureclass to XML Workspace tool available in ArcGIS Pro. This preserves the coded value domains assigned to the data fields. Step 2: Add the data field AssetCatalogID to both the asset catalog table and the asset layer The AssetCatalogID field should be a short integer field to eliminate the issue of trailing and leading spaces when querying the table for the record. Step 3: Populate the asset catalog tables with asset information. Step 4: For each asset layer to query the asset catalog tables, create a coded value domain with a listing of all asset catalog entries. The code of the coded value domain will be used to query the asset catalog record containing the utility known information about the asset. Asset Layer assetcatalogid = asset catalog table assetcatalogid This coded value domain needs to be assigned to the “assetcatalogid” field which was added to the asset layer in step 2. The description of this coded value domain will be what field users see when selecting an asset catalog item to describe the newly constructed asset When working with a subtype heavy asset layer such as PipelineJunction (enterprise) has a separate subtype for each type of fitting. A separate coded value domain should be used for each subtype (ie. type of fitting). This shortens the picklist presented to the field user. These different coded value domains can still query the same asset catalog table. Step 5: Assign the arcade script to query asset catalog table The last piece of this configuration of Field Maps is to use the ArcGIS Field Maps web application to assign a form expression to the asset layer field to be automated. In this example that will be the manufacturer field. Here is an example of the form calculation to assign to manufacturer: //Form Calculation:  Pipe_Barcode_Manufacturer //Description: Read the BARCODE, then decode and populate the MANUFACTURER value from the BARCODE value //Description: If an ASSETCATALOG value is entered, query the AssetCatalog Pipes table to retrieve MANUFACTURER value. //Field:  MANUFACTURER //Edit scenario 1: A barcode has been entered if ($feature.barcode != null)     return mid($feature.barcode,0,2) //Edit scenario 2: No barcode, no Asset Catalog entry   else if ($feature.assetcatalog == null)    return ($feature.manufacturer) //Edit scenario 3: No barcode, AssetCatalog value has been entered var assetcatalogId = $feature.assetcatalog; if (assetcatalogId == null) {     return; } //Query assetcatalog table to retrieve MANUFACTURER values var cuTable = FeatureSetByName($map, "AssetCatalog Pipes", ['manufacturer'], false);   //Filter the selected Assetcatalog table records based on assetcatalogid value //Use the first record returned from the query var cuAttribute = First(Filter(cuTable, 'assetcatalog  = @assetcatalogId')); if (cuAttribute == null) {     return; } else {     return cuAttribute.manufacturer     } With the asset catalog tables deployed and the form expression in place to query the table, this automation is ready to put in the hands of your field users. Going to the Field The user experience is very intuitive for the field user. Simply tap on the Asset Catalog data field.  This will open the coded value domain list.  The field user taps on the desired type of asset to select from the list. Once selected, the form expressions will immediately initiate. This will populate the edit form with the asset catalog table retrieved data. With the steel asset data retrieved and populated, the field user can focus on completing the rest of the edit form. Automating Data Entry The gas and pipeline industry has long struggled with how to automate the documentation of new steel pipe construction. Lookup tables in ArcGIS Field Maps is one approach to solving this inefficiency and additional cost. Using lookup tables is a very straight forward method for automating data entry by field users. This method of automation is applicable to many instances where field users are being asked to enter information that the organization already knows. About This Blog Series This blog article is the third in a series of five blog articles. Upcoming blogs will continue explaining in greater detail how to configure the Esri ArcGIS Field Maps mobile application to deploy these examples. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

The attached style file contains the latest version of the symbols designed for deployment with the Utility and Pipeline Data Model (UPDM). These symbols are synchronized to UPDM 2021 and it's asset group and asset type unique value combinations. ... View more

IT Needs Steel Toed Boots   By Tom DeWitte and Tom Coolidge What is it like to be a field worker at a utility? Given that over 70% of a utility’s organization is either directly supporting field workers or physically spends their day in the field, this is a question to which all utility staff need to know the answer. When engineers and information technology (IT) professionals put on their hard hats and strap on their steel toed boots to head to the field what will they find? An incompatible mix of old and new. The New In the field they will find field workers using new advanced Bluetooth-enabled mobile sensors such as GNSS receivers, electro-magnetic locating devices, and methane gas detectors. They also will find personal phones with built-in cameras, compasses, and location capabilities. The Old The output of those communication-enabled devices will be written down on paper. If paper is not available, it will be written on the back of the worker’s hand. The camera photos of inspections and assets will be emailed to their work email or someone in the office. The emailed data will then be manually associated to the inspection or asset it is documenting. Field Work is Digital Work Today’s mobile sensors, when combined with a nearby mobile device and the correct mobile GIS application on the mobile device, create a wonderful opportunity to transform tasks and workflows performed in the field. This transformation can overcome, if not eliminate, the inefficiency inherent in today’s incompatible workflows. The communication capable mobile sensors have been or will soon be deployed at most utilities through simple replacement of hardware.  The deployment of mobile devices and mobile GIS applications to consume the mobile sensor data to complete the field work transformation to digital work is very much a work in progress. This is where many utility IT departments are struggling. This is where steel toed boots are required. Work Happens Out of the Truck Getting IT into their steel toed boots and out into the field is a critical step. Spending time in the field is needed to secure the foundational understanding that work happens out of the truck. Field work is not a laptop on the hood of a pickup! Field work is a locator walking a city block to mark the next phase of a telecommunication direct bore project. Digital field work is recognizing that besides spray painting the ground to locate the buried pipe, photos and videos need to be taken, with GPS coordinates where possible, to accurately document where the locate marks were placed. Field work is using a methane gas detection sensor to crisscross someone’s front yard to locate a gas leak.  Digital field work is having each individual barhole methane reading automatically combined with a GNSS receiver defined location and transmitted directly to the GIS system to auto-populate the gas leak report. Field work is wandering around an area trying to remember where a gas valve is located so you can use a paper form to document a valve inspection to assess its condition. Digital field work is using your mobile device’s built-in compass with your mobile GIS application to direct you to the valve, then complete a digital form and use the mobile device’s camera to take a photo of the valve to document its current condition. The mobile GIS application completes this task by having that photo automatically associated to the asset record and transmitted to the GIS system. None of these field work tasks occur in or near the truck. All these tasks involve the field worker in motion to complete the task.           It’s Stuck in the Truck In the late 1990s and early 2000s, ruggedized laptops started to show up in utility vehicles.  For safety purposes these laptops were and still are predominantly mounted into the truck dashboard.  This is great for field tasks such as completing timesheets, receiving, and viewing work orders, driving navigation assistance, and map viewing. Truck-mounted laptops struggle to add value to the digital work tasks which occur outside of the truck. This is especially true for workflows which use mobile sensors. Bluetooth communication is limited to a range of about 30 feet in the best of conditions. Imagine how a customer would feel if a utility worker drove their truck onto their yard so the methane gas mobile sensor can be in range to transmit its readings to the truck mounted laptop. Mobile Devices for Mobile Tasks The hard truth is that to achieve the promised dream of improved productivity and data quality that is supposed to come with a digital transformation, you need a mobile device such as a tablet or phone for mobile tasks. Digging deeper into what it takes to achieve the digital transformation dream is a mobile GIS application which can easily integrate with the mobile sensors. The digital transformation premise is based on the idea that information is captured once. No repeats. Writing field collected data down on paper or the back of your hand so it can be transposed into a device in the truck will not achieve the promised productivity. Mobile tasks require nearby mobile devices running mobile GIS applications. Mobile Apps for Capturing Mobile Sensor Data It is the mobile GIS application running natively on the mobile tablet or phone which enables the “capture once” mission of digital transformation. It is the mobile GIS application which combines the GNSS receiver Bluetooth data feed with the mobile device’s compass that points the way for the field worker to find the buried valve. It is the mobile GIS application which receives the locating estimated depth, coordinate location, photos, and video, then transmits them directly to the GIS. It is the mobile GIS application which combines methane gas detection measurements with GNSS receiver location and completes the digital leak report form, then transmits it directly to the GIS system. It is the mobile GIS application running on the mobile device which allows the field worker to capture the location of the newly installed pipe segment using a sub-foot GNSS receiver Bluetooth data feed while walking along the trench or direct bore path. Since humans currently only have two arms and two hands, none of these examples is going to be accomplished with a ruggedized laptop. If one hand is supporting the laptop and the other hand is holding the mobile sensor, whose hand is doing the typing? There is a reason why mobile tablets and mobile phones with touch screens are the platform of choice for mobile GIS applications. IT to the Field When engineers and IT professionals’ dust off their hard hats and pull their steel toed boots out of the back of the closet to head to the field is when the digital transformation dream will accelerate for field workers. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions ... View more

Scanning and Decoding Barcodes Part 2 of 5 By Tom DeWitte and Tom Coolidge Our first blog of this series provided an overview of the steps a utility can take to improve the productivity of the utility field worker. If you missed it, you can access it here. In this blog article, we will dig into the first step in automating field data collection. The first step in making life easier for the utility field worker is to deploy a configuration of ArcGIS Field Maps that minimizes the amount of manual data entry they must perform. As noted in the previous blog article, this is the first of four steps to automating field data collection. Minimize manual data entry Auto-populate what is already known Leverage sensors on your mobile device Use geography The use of barcodes to automate data entry is one method to minimize manual data entry. Barcodes Barcodes are currently used for many purposes across utility industries. Most utility field workers will have a barcode on their employee badge. This barcode encodes the unique identification of the employee. Another common use is to barcode machinery. This barcode encodes the manufacturer information about the device. Then there is the use of barcoding assets. In the natural gas industry, barcodes are applied to the plastic pipe, plastic device, or plastic fitting by the manufacturer. In industries that do not have a barcode industry standard, there are utility companies which are placing their own barcodes onto assets as they enter the warehouse. Barcodes are on many assets today, and soon seemingly will be everywhere. Simply having a barcode does not directly equate to productivity gains for the utility field worker. There needs to be a companion capability. This companion capability includes electronically capturing the barcode, and software to decode the barcode, then auto-populate the information directly to the asset record. Without this companion capability the utility field worker will have to manually read the 16-character case sensitive text string and without error manually enter it into the asset record. Manually entering barcodes is slow, prone to error, and a frustrating experience for field workers. Scanning the Barcode Two predominant methods for electronically capturing a barcode are optical and infrared scanning. Optical scanners are the camera built into your mobile device. Infrared scanners are external devices which Bluetooth connect to your mobile device. ArcGIS Field Maps supports both methods. If interested in using a handheld infrared barcode scanner, the Bluetooth device needs to support the keyboard wedge method for integration with ArcGIS Field Maps. Regardless of barcode scanning method, when ArcGIS Field Maps electronically captures a barcode the designated text field in your form will be automatically populated. There is no manual data entry. With the barcode now electronically captured and stored in the BARCODE field, software needs to be employed to decode the barcode value and auto-populate the appropriate data fields. Decoding the Barcode In many examples this decoding of the barcode can be accomplished with a small set of Arcade scripts. Each attribute which will be auto populated from the information encoded in the barcode will have an Arcade script. Deploying the Automation The method used to embed the software capability to decode the barcode in ArcGIS Field Maps is done through configuration. The Field Maps Web Application provides the administration environment to perform this configuration. The web application is used to define the Arcade script and the ability to apply this script to the table field. Each field to receive information from the decoded barcode values will have its own Arcade script. Field User Experience With these scripts now configured into the editing behavior of the layer, the automation is in place for the utility field worker to utilize. For the utility field worker, the field data collection is very simple. Open ArcGIS Field Maps and select the web map designated for the specific data collection task. Now you are ready to collect. The collection process with barcodes is to select the item to be collected and capture the barcode. The ArcGIS Field Maps application will automatically run the Arcade scripts immediately after the BARCODE field is populated. This allows the utility field worker to immediately be able to review the decoded content and verify it matches what was installed. As the above screenshot shows, a total of 8 data fields were automatically populated from information embedded in the BARCODE field. Including the BARCODE field, a single barcode scan results in nine data fields being populated with no user typing. Automating Data Entry The use of barcodes is only one example of how ArcGIS Field Maps can be used to free your utility field workers from manual data entry. Other opportunities to improve the productivity of utility field workers include:                 -auto-population of the date/time when the collection was performed                 -auto-population of who performed the data collection                 -auto-calculation and population of a pipe’s volume and surface area                 -auto-population of the projectID based on the asset’s location intersecting a project polygon                 -auto-population of the nearest address, based on the asset’s location These are just a few examples of how the automation capabilities in ArcGIS Field Maps can be used to improve the productivity of the utility field worker. About This Blog Series This blog article is the second in a series of five blog articles. Upcoming blogs will continue explaining in greater detail how to configure the Esri ArcGIS Field Maps mobile application to deploy these examples. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more

Part 1 of 5 By Tom DeWitte and Tom Coolidge Utilities collect a lot of data. This means utility field staff are spending a lot of time filling out forms.  Many companies today are undertaking efforts to convert paper forms to digital forms.  The basic justification for this effort is to eliminate the duplicate data entry of having an office person read, interpret, and recreate in the corporate enterprise systems what is captured in the field. But what about the field staff themselves, where is their benefit of digital transformation?  This blog series is about how to improve the productivity of field staff - how to automate data entry, leverage mobile device sensors, utilize intelligent software, and truly reduce the amount of time field staff spend filling out forms. Making life easier for field staff Have you ever met a utility field worker who walks into the office in the morning and says “Boy, I can’t wait to fill out forms today?” No, well me either. What is common to hear field workers complain about is spending too much time completing paperwork. The data utility field staff collect is vital to the successful operation and engineering of the utility system. Asking the field staff to stop collecting data is not an option.  But what about creating forms that auto-populate themselves to the maximum extent possible?  Stop typing The first step in making life easier for the utility field worker is to deploy solutions which minimize the amount of manual data entry they must perform. Today’s mobile devices and applications provide a wide range of capabilities to capture a large amount of information with minimal effort by the utility field worker. An example of this is barcodes.  The natural gas industry uses the ASTM F2897 barcode standard for its plastic pipe, fittings, and devices. A field worker equipped with a mobile application on a smart phone or tablet can use the device’s   camera to capture the barcode. This automatically inserts the barcode into the form. Then the mobile application can decode the information embedded in the barcode and auto-populate the appropriate form fields. If you are keeping score that is 8 form fields auto-populated and zero manual data entered for the utility field worker.  Barcodes can also be used on a worker's badge. Use the mobile device camera to read the badge and auto-populate the worker’s information into the form.  Take this idea a step further and have the mobile application compare the scanned worker ID against a table of operator qualifications to instantly verify that the worker has the current valid qualifications for performing the work, such as a weld or a plastic fusion. All of these intense data documentation and validation steps can be performed with no manual data entry.   Auto-populate what is already known The second step in making life easier for the utility field worker is to stop asking them to enter information the organization already knows. An example of this is project data.  Before a utility field worker drives up to a construction site, the project information is already well known within the utility planning, engineering, and permitting departments. A common utility practice is to create a project polygon to define the extent of the construction area. When using a geography-based mobile application this project polygon can be referenced to automatically insert project information into the form by having the field utility worker simply be within the extent of the project area. Another example is asset condition inspections, such as a valve inspection.  It is very common for a valve inspection form to ask for information about the valve. What size is it? Who was the manufacturer? What type of valve? The organization should already know the answer to these questions. The utility field worker simply needs to verify that the organization information is correct.  In this example the geography-based mobile application enables the utility field worker to simply click on the valve on the map to initiate the valve inspection. By selecting the valve from the map, the form automatically retrieves the information from the valve record and auto-populates the valve information portion of the form. All the field worker must do is review the information to verify it is correct. Asset Catalogs Another method for auto-populating what the organization already knows are lookup tables. When documenting new construction, these lookup tables are called Asset Catalogs.  An Asset Catalog record contains the manufacturer specifications for an asset. For example, when installing a steel pipe, the organization already knows the nominal diameter, wall thickness, outside diameter, material, manufacturer, manufacture type, specified minimum yield strength (SMYS), and pipe coating type to name a few of the known characteristics.   When a mobile application can leverage a lookup table, the utility field worker experience is very straightforward.  Select the installed type of steel pipe from a picklist. The mobile application then uses the selected item to query the asset catalog table. The selected asset catalog table is read, and the information is used to auto-populate the new steel pipe record. Review the now populated asset information to verify it is correct. The mobile user has populated multiple data fields by only manually selecting a single value from a picklist. Once again, no typing is required. The mobile sensor array The third step for making life easier for the mobile field worker is to leverage the many sensors of your mobile device. Most phones and tablets available today come with a built-in GPS chip. When you have a geography-based mobile application which can leverage that GPS, it can do much more than simply place a dot on the map to show you your location.  The geography-based mobile application can auto-populate your form location descriptors such as address, city, state, zip code, and utility division. Area based descriptors of location such as utility division, city, state, and zip code can be determined by having the software automatically perform a point on polygon overlay using the GPS location as the point location. Some geography-based applications can also use the GPS location to perform a reverse geocode operation to determine the address. In both examples, the software automatically populates this information when the field worker taps on the screen to capture the GPS location. No other user input is required. Use geography to automate The fourth and final step for making life easier for the mobile field worker is to leverage geography. There are many examples in utility field data collection where multiple assets or locationally unique items need to be grouped together. A pressurized pipe system example is pressure test documentation. After construction of the pipe system, that new or modified section of pipe must be pressure tested to verify it will not leak. This documentation step requires that all assets which were part of the pressure test be grouped together and assigned a common Pressure Test ID. This can be a very time-consuming documentation step as a single pressure test can include dozens of individual assets. With a geography based mobile application the utility mobile worker can draw a polygon to encompass the assets which were pressure tested. The geography-aware mobile application automatically uses the utility field worker defined polygon to select all pipe segments, fittings, and devices within the polygon. Each selected asset is assigned the pressure test ID. Improve data quality and completeness These examples of how to make life easier for utility mobile workers also have a benefit for the office staff. This auto-population provides a more complete record of the asset. Pipe asset values such as wall thickness and SMYS are often not considered values which are required to be entered by the field worker. Human nature is that anything not required likely will not be populated. Yet, these values are critical to engineers determining the range of safe operation of the pipe network. Conclusion Digitally transforming utility field data collection needs to be more than creating a digital form to improve the productivity of the field staff.  It needs to automate data entry. These forms need to leverage mobile device sensors, utilize geography-aware mobile applications, and truly reduce the amount of time field staff spend filling out forms. About This Blog Series This blog article is the first in a series of five blog articles. Upcoming blogs will explain in greater detail how to configure the Esri ArcGIS Field Maps mobile application to deploy these examples. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions.   ... View more

ArcGIS for District Energy: Tracing Thermal Energy By Tom DeWitte and Tom Coolidge The purpose of a district energy system is to transport thermal energy to customers (district heating) or to transport thermal energy away from customers (district cooling). It sounds simple, yet the looped nature of district energy pipe networks makes them some of the most complicated utility pipe networks. Modeling flow through this complicated network of energy plants, pipes, pumps, valves, and eventually buildings is not easy. Yet, it is vital to planners, engineers, and operators of the pipe network to understand how their product moves to and from their customers. This gets even more complicated if the district energy organization utilizes circulation zones with heat exchangers. In that system configuration, the water flow is not the same as the thermal energy flow. This requires an application and data model smart enough to differentiate between water flow and thermal energy flow. This is where ArcGIS with its ArcGIS Utility Network capability and District Energy Data Model can help.  Thermal Energy and District Heating When modeling a district heating pipe network, it is vital to understand where the energy starts and where it goes. For district heating, the start is typically the energy plant. From the energy plant the heated water or steam transports the thermal energy through pipes, pumps, heat exchangers, valves, more pipes and eventually it to a building. The customer in that building consumes the thermal energy to heat their home. In a full loop system, the now cooled water returns to the energy plant to be reheated. Thermal Energy and District Cooling When modeling a district cooling pipe network, the thermal energy starts with the customer and is delivered to the cooling plant where it is typically released into the air. In a full loop system, after the thermal energy is released to the air, it is sent to chiller units to further remove thermal energy. This results in an additional decrease to the water temperature. Once cooled it is transported through pipes, pumps, heat exchangers, valves, and more pipes before it reaches the customer's building. At the building the chilled water absorbs the customer’s waste heat and transports it back to the cooling plant. Leveraging Utility Network Modeling this real-world transportation of thermal energy through a pipe network, requires more than an understanding of how the pipes, pumps, heat exchangers, valves and other components are connected. It requires the ability to understand which pumps are operating, and which valves are closed. It also needs to differentiate between cathodic protection wires and leak detection wires. These wires are connected to the pipes but do not transmit thermal energy. To accurately represent these additional real-world complexities, we need a more advanced connectivity model. We need to leverage the Utility Network. The Utility Network is an extension to ArcGIS. ArcGIS is the geographic information system (GIS) provided by Esri. What Stops Thermal Energy Flow With a Utility Network comes the Trace geoprocessing tool. A configuration of this tool is what will be used to perform the thermal energy flow trace. To correctly configure the thermal energy flow trace requires a real-world understanding of what can stop the thermal energy flow. In the real-world devices which are closed, such as a valve, or are not operating, such as a pump, will impede the flow of the thermal energy. Add to this list any pipe segment or device which is not in service, such as retired pipe segments or pipe segments which are proposed but have not yet been built. Lastly, there is the need to exclude the cathodic protection wires and leak detection wires which are part of the pipe network but do not conduct thermal energy flow. When using the District Energy Utility Network Foundation data model, those constraints look like this: Pipe segment or asset is not in service: Lifecycle Status Does not equal In Service Valve is closed: Device Status is equal to closed Pump is not operating: Device Status is equal to closed Cathodic Protection wires: Category is equal to CP Only Leak detection wires: Category is equal to Leak Detection Only Configuring the Trace Tool The Trace geoprocessing tool in ArcGIS Pro has many parameters. Here is how to transpose the constraints into the specific settings in the Trace tool. The type of trace will be a downstream trace, leveraging the DHC domain network, and the DHC Energy Tier. Setting the Tier to “DHC Energy Tier” is important as it sets the flow source as the energy plant/chiller plant, versus the “DHC Pressure” tier which would set the source as in-system pumps. The constraints will be added as Traversability Barriers. If any one constraint is true, the trace will not traverse beyond the asset. When this trace is run, it will return all pipe segments, devices, fittings, and customer service points which are receiving thermal energy from the designated start location. This includes both the supply and return portions of the pipe network. If you are a district heating organization and only interested in the thermal energy flow supplying energy to the customer, you can add a filter barrier: Pipe segments are only supply lines: Line Asset Type does not equal supply This will return a selection set of the pipe network which shows how the thermal energy traverses the pipe network from the designated location to the customer. The same configuration will work on the district cooling pipe network. Sharing the Trace Now that you know how to configure the trace tool to perform a thermal energy flow trace, how do you share this with others in your organization. And, how do you share it in a way that does not require everyone to manually perform this configuration of the Trace Tool. This is where the new functionality introduced at ArcGIS 10.9, called Trace Configurations is useful. Trace Configurations is the ability to store a configuration of the Trace Tool within the Geodatabase. When the Thermal Energy Flow trace is stored in the Geodatabase, other desktop, web, and mobile users do not need to know how to configure the tool. A simple check of the “Use Trace Configuration” option removes all the configuration options and replaces it with a simple pulldown menu for the end user to select from. Having the trace configuration centrally stored and accessible to end users ensures that everyone is running a properly configured thermal energy flow trace. Summary Planners, engineers, and operators require this type of advanced flow modeling to help them perform their daily activities. Thermal energy flow modeling is just one of the many types of water, thermal, cathodic protection, leak detection flow analysis which can be configured with the ArcGIS Utility Network.  These trace capabilities help to remove some of the complexity of maintaining and operating a district energy pipe system. PLEASE NOTE: The postings on this site are our own and don’t necessarily represent Esri’s position, strategies, or opinions. ... View more