Abyss – Machine Learning Algorithm

The Issue at Urban Utilities

Automated closed-circuit television (CCTV) defect identification. QUU conducts regular inspections of its sewerage mains via CCTV. The subsequent review of footage and condition assessment is undertaken manually, is resource-intensive and time-consuming. Seeking an automated solution, which can code and score asset defects, and points of interest, in accordance with the Water Services Association of Australia?s (WSAA) WSA 05-2008 Conduit Inspection Reporting Code of Australia.

The condition assessment of sewers and maintenance structures must comply with the Water Services Association of Australia?s (WSAA) WSA 05-2008 Conduit Inspection Reporting Code of Australia. The Code includes codes to describe defects, a scoring system that recognizes different relevances of particular defects on rigid and flexible pipes, revised structural and service grading thresholds, and acceptance limits for defects for newly constructed sewers.

Urban Utilities conducts regular inspections of its sewer mains via CCTV. The subsequent review of footage and condition assessment is undertaken manually, is resource-intensive and time-consuming.

The Solution

Trial and assess Abyss Solutions’ machine learning algorithm, and its ability to reduce the time required to review footage and its potential to automatically identify and code defects.

The Pilot

The trial was conducted in two phases:

Phase 1 – Urban Utilities contributed 3 kilometers (1.86 miles) of CCTV footage of AC and VC sewer reticulation network. Abyss applied their machine-learning algorithm to this footage to produce a condensed view of only the segments containing defects.

Phase 2 – The ability of the machine learning algorithm to automatically classify/code defects.

Pilot Results

Urban Utilities invested AUD101,000 (USD70,000) of which 50% was funded under arrangements delivered in the Grant Deed between the State of Queensland and State of Nevada. Phase 1 at AUD15,200 (USD11,000) and Phase 2 at AUD86,000 (USD59,000).

PHASE 1

Urban Utilities contributed 3 kilometers (1.86 miles) (64 inspection videos, 12 hours) of CCTV footage of our AC and VC sewer reticulation network. Abyss applied their machine-learning algorithm to this footage to produce a condensed view of only the segments containing defects. The automated algorithm was used to produce fault detections. The faults were classified by a human auditor, a civil engineering expert from Aurecon, who was new to the Abyss tool. Commentary provided by Aurecon has been used as a benchmark for performance evaluation.

Phase 1 – time taken assessment. The manual review 3 hours of footage took 2.5 hours to annotate (83% of the video time), while the Abyss extract tool 6.5 hours of footage took 2 hours to annotate (31% of the video time). The time taken comparison for Phase 1 shows an efficiency gain of 63%.

Phase 1 – accuracy assessment. 3 hours of footage set aside for evaluation. The algorithm detected 26 faults and missed 14 faults. It was noted that 50% of the videos in the validation batch were heavily overexposed due to the unusually bright light on the camera. It is acknowledged that the over-exposed footage did impact accuracy.

Based on the outcome and feedback, Urban Utilities directed Abyss Solutions to proceed with Phase 2. Urban Utilities also agreed on an amendment to Phase 2, asking Abyss Solutions to focus resources on further training of the algorithm to improve the accuracy in detection and ability to automatically code some of the more common defects.

PHASE 2

By the end of Stage 4, the Abyss extract tool was able to accurately identify 87% of all defects contained in the CCTV footage and was found to enable the user to complete the task of assessing the CCTV footage 2.3 times quicker for a novice user and 3-5 times quicker for more experienced users than the current fully manual method, providing higher audit consistency and reducing fatigue. Abyss Solutions also has demonstrated the fault classification on the examples of joint displacement and root detection with the respective accuracies of 82% and 85%.

Further Adoption

The adoption of this technology as a business-as-usual solution and integration in the Urban Utilities workflow is under consideration.

About the Technology

Abyss Solutions, located in Sydney, Australia was founded by four scientists and engineers from The University of Sydney in 2014. Abyss is a robotics company that combines the latest innovations in ROUVs with state of the art data analytics to provide a safer, easier, and more comprehensive underwater inspection, allowing for correct asset management decisions.

http://abysssolutions.co

 

Abyss – Drinking Water Reservoir Inspection

The Issue at Urban Utilities

Reservoirs perform an integral function in the storage and delivery of a safe drinking water supply to our customers. The structural condition of the reservoir is perhaps the largest aspect of how it may perform overall in its ability to store drinking water.

The internal inspections of reservoirs can be problematic. Depending on the criticality of the reservoir the asset cannot always be emptied or taken off-line. Current inspections are undertaken by divers, which makes this a costly activity.

The Solution

Deploy an ROUV to capture both above water and underwater footage.

The Pilot

The inspection was conducted over two consecutive days. The scope included:

  • internal inspection of the reservoir through the provision of tethered drone, above and below water,
  • location/identification of interesting features/features of concern,
  • detection of any foreign matter,
  • amount of sedimentation on the floor,
  • condition of internal fixtures and features,
  • detection of ingress points,
  • condition assessment report, and
  • production of a 3D digital model.

Pilot Results

Urban Utilities invested approximately AUD40,000 (USD28,000), of which 50% was funded under arrangements delivered in the Grant Deed between the State of Queensland and the State of Nevada.

The ROUV was deployed from the access hatch on the top of the reservoir. The underwater inspection was undertaken using the submersible ROUV fitted with the Abyss Solutions imaging technology, which comprises a computer vision camera, integrated lighting, and data capturing software. This allows high-fidelity data representation in turbid and low light environments.

The ROUV was also piloted on the surface of the water with an upward-facing camera. Any sunlight-visible was identified and noted as locations of possible ingress.

Abyss Solutions delivered the outcomes of the inspection via a reservoir condition database, web-accessible. The database also enables the download of a printable PDF report. The database houses:

  • reservoir characteristics, including:
    • reservoir details (year built, location, location coordinates)
    • capacity (volumetric, contents, dimensions, water level)
    • construction profile
    • access profile
  • inspection details (date, time, team, weather conditions)
  • scoring guide/legend
  • overall reservoir condition score.

Abyss Solutions also provided a condition assessment and score for individual reservoir elements:

  • access hatch & ladders,
  • floor level outlet,
  • overflow outlet & inlet elbow,
  • inlet pipe, pedestals & straps
  • scour outlet & channel,
  • columns & walls,
  • water stop & concrete lip,
  • telemetry sensors,
  • mixer unit,
  • roof soffit & purlins, and
  • floor

A multi-criteria condition assessment based on the IPWEA Condition Assessment & Asset Performance Guidelines was applied to the reservoir. Each element was been assigned a condition grade ranging from ?0-not rated? to ?5-very poor?. A weighted average was used to assign the overall reservoir condition. High fidelity imagery accompanies the assessment of each reservoir element.

Abyss Solutions also constructed a 3D digital model showing the internal configuration of the reservoir. The model was produced using data from the inspection. The model provides a 3D fly-through of key reservoir components with embedded imagery, and annotations. The method of delivery is via a portal, with a report that can be downloaded, exceeded expectations.

Further Adoption

On the back of this successful trial, Urban Utilities self-funded an inspection of another drinking water reservoir. Adoption of this technology as a business-as-usual solution is under consideration.

About the Technology

Abyss Solutions, located in Sydney, Australia was founded by four scientists and engineers from The University of Sydney in 2014. Abyss is a robotics company that combines the latest innovations in ROUVs with state of the art data analytics to provide a safer, easier and more comprehensive underwater inspection, allowing for correct asset management decisions.

http://abysssolutions.co

 

Abyss – Underwater Sewerage Inspection

The Issue at Urban Utilities

The Norman Creek siphon (Brisbane, Australia) was refurbished in approx. 1974.? It is designed to transport sewage under the Brisbane River into the S1 trunk system to Eagle Farm Pump Station, and then on to the Luggage Point Sewage Treatment Plant.?

The siphon runs under the Brisbane River from Norman Creek to New Farm, and comprises two concrete shafts which run deep underground with the horizontal section beneath the Brisbane River approximately 318 metres long (1,043 feet). The current water levels are approximately 36 meters-39 meters (118-128 feet) below the access point.

The siphon is currently filled with potable water, instead of being in its dry state.? As a result, the asset cannot be inspected via traditional means. The condition of this asset is unknown, and sending divers to inspect the asset presents a significant safety risk.

The Solution

Deploy a ROUV to capture closed-circuit television (CCTV) footage and still images of the asset.

The Pilot

The pilot was conducted in two phases. Phase 1 was an exploratory activity to determine the feasibility of deploying a tethered drone into the siphon. Phase 2 included:

  • Internal inspection of the siphon through the provision of tethered drone
  • Location/identification of interesting features/features of concern
  • Condition of internal fixtures and features
  • Detection of ingress points
  • Condition assessment report
  • 3D model

Pilot Results

Urban Utilities invested approximately AUD70,000 (USD42,000) of which 50% was funded under arrangements delivered in the Grant Deed between the State of Queensland and State of Nevada.

The underwater inspection was undertaken using a submersible fitted with the Abyss Solutions imaging technology, which comprises a computer vision camera, integrated lighting, and data capturing software. This allowed high-fidelity data representation in turbid and low light environments. A site inspection was undertaken to determine access conditions and water quality parameters.

The submersible was lowered down two access shafts and controlled through a tether by a pilot located on the surface. The submersible navigated along the obvert of the tunnel, with a downward-facing camera that captured high fidelity images of the visible surfaces of the twin pipelines.

Abyss Solutions delivered the outcomes of the inspection via a web-based database. The database houses:

  • siphon characteristics, including:
    • details (location, location coordinates, length, and diameter)
    • construction profile
    • access profile
  • inspection details (date, time, team, weather conditions)
  • scoring guide/legend
  • overall siphon condition score

Abyss Solutions also provided a condition assessment and score for individual elements:

  • tunnel walls
  • mild Steel Cement Lined (MSCL) pipes & protective coating
  • pipe supports
  • submarine cable

A multi-criteria condition assessment based on the IPWEA Condition Assessment & Asset Performance Guidelines was applied. Each element was assigned a condition grade ranging from ?0-not rated? to ?5-very poor?. A weighted average used to assign the overall reservoir condition.

Abyss Solutions also constructed a 3D digital model showing the internal configuration of the siphon. The model was produced using data from the inspection and includes annotations. The method of delivery via a portal exceeded expectations.

Further Adoption

The adoption of this technology as a business-as-usual solution is under consideration.

About the Technology

Abyss Solutions, located in Sydney, Australia was founded by four scientists and engineers from The University of Sydney in 2014. Abyss is a robotics company that combines the latest innovations ROUVs with state of the art data analytics to provide a safer, easier, and more comprehensive underwater inspection, allowing for correct asset management decisions.

http://abysssolutions.co

 

AboveGeo

The Issue for Large Farms

An important issue in the agricultural sector is the time and resources it takes to manage pest control, weed control and crop stress monitoring over very large areas of land. More and more farmers are looking towards new technology such as Unmanned Aircraft Systems (UAS) to drastically reduce the time it takes to manage these issues, manage them more effectively and save resources. Rather than having growers evaluate fields manually on foot or by tractor, this technology allows farmers to gain immediate knowledge about the status of their fields in shorter periods of time. This information can now be gathered whenever and wherever it is needed, minimizing the response time required to address issues and maintain crops.

Winnemucca Farms is the largest single integrated farming operation in Nevada and one of the largest in the U.S. They have approximately 28,000 acres of land available for farming located across two valleys. The Winnemucca farm manager was using manned aircraft to acquire color infrared images of the fields. These images didn’t have the detailed spatial or spectral resolution that can be acquired from UAS with multispectral and standard color sensors.

The Desert Research Institute (DRI) and AboveGeo (a UAS technology company) met with the Winnemucca Farm Manager to discuss their current image products from manned aircraft image collection and what additional data would be of benefit to them. Winnemucca Farms typically purchases color infrared images as hard copy products, that do not have sufficient spatial resolution or overall image quality to provide the level of information for the management decisions. High quality images with fine spatial resolution would provide more detailed information on small areas of crop stress much earlier. Specifically, the farm manager stated that a one-time high spatial resolution set of images depicting elevation differences as shaded hillslope images would be helpful, but a more beneficial product would be the Normalized Difference Vegetation Index (NDVI from red and near infrared bands) image depicting crop health at critical times, as well as derivative estimates of total crop cover acres per field.

The Solution

The term “UAS” is preferred over “drone”, because “drone” is the term that was used in World War II for dummy unpiloted aircraft that were sent up into the air without much control, which were then shot at for target practice. UAS, unmanned aircraft systems, is a much more sophisticated platform with a suite of available sensors, so NASA and other organizations prefer using the term “UAS.” UAS can also be defined as Unmanned Autonomous System, which would refer to either ground and air based vehicles.

One of the great advantages of the UAS is the detailed imagery it provides, which is what was lacking at Winnemucca Farms. Because the system is flying low over the field and mosaicking very detailed images (e.g., cameras that have 20 mega pixel versus five megapixels), it allows you to capture much more detailed imagery. This is what the UAS brings as a solution. In addition to this, through computer-aided data analysis, DRI also created shaded hillslope imagery that provided a 3-D view of the elevation differences within the field. “This is something that the Winnemucca farm manager told us was of high value to him,” according to Lynn Fenstermaker, Biology Research Professor at DRI.

Several Nevada companies were approached (Alaska Aviation Proving Ground, Inc., VeraScan and AboveGeo, formerly AboveNV) and based on the study site location, company UAS fleet and availability, AboveGeo was selected to participate in this project.

What this technology does is it gives the farm manager an opportunity to fine tune the amount and placement of water, herbicides and/or pesticides so that they’re not applying the same rate to the entire field. This allows the farm managers to reduce costs by reducing the amount of pesticides, herbicides and water applied to each field and each of these applications have associated costs. In the case of water, if used in low spots where water is going accumulate, the amount of water applied to these areas can be reduced by either increasing the speed of the center pivot irrigation arm or decreasing the amount of water to be applied. The farmers can then preferentially apply water, herbicides and pesticides to the areas where it’s most needed and thereby cutting down on overall costs and conserve water.

Pilot Background

This was a NV Governor’s Office of Economic Development Knowledge Fund project that was jointly funded by WaterStart and the overall Knowledge Fund. The Desert Research Institute was interested in working with a couple of farms on the project, but only received one willing to participate, Winnemucca Farms. Winnemucca Farm’s chief administrative officer, Samuel Ralston, was at the time a member of the WaterStart board of directors and helped facilitate the project.

The specific goal was to conduct research to determine which platforms and sensors would be able to provide data of value to farm managers, with a particular focus on addressing drought, irrigation, water stress, weed and pest related issues. The project tested the capabilities of different sensors and different platforms such as fixed-wing vs. multirotor UAS and standard color versus multispectral cameras. The research was conducted primarily on alfalfa, peas and potato fields.

DRI tested the applicability of UAS data to address large-scale, multi-crop agricultural needs, particularly related to herbivory, salinity and water-related crop stress. The main goal was to use UAS data acquisition to identify and map agricultural crop stress that will lead to improved water use while maintaining and/or improving crop yields.

DRI provided imagery, made it available on a website as well as providing hard copies for the farm manager. According to DRI, they received a lot of support from Winnemucca Farms in this project regarding information needed on planting, when the crops were emerging and what were the best times of the growing season to capture imagery so that they could capture maximum crop stress. The majority of the deliverables in this project were to provide imagery, although there was one case in which DRI provided data sets regarding estimated value of crop loss due to herbivory. DRI estimated the area of lost or low yield and then the value of that crop loss.
DRI conducted the pilot project from June 9th 2016 through September 12th of 2017 and they conducted seven field trips where UAS imagery was acquired, four data acquisitions in 2016 and three in 2017.

Pilot Results

Multiple UAS flights were planned and completed during the 2016 and 2017 growing season at Winnemucca Farms. Flight acquisition dates included the following for each year:
 2016: June 9; July 7-8; August 11-12; and September 7
 2017: April 1, August 1 and September 12

For each date of UAS operations, imagery for the entire 130 acres of each field (selected by the farm manager) were acquired. All fields are round center-pivot irrigated fields and AboveGeo acquired imagery, both standard color and multispectral imagery over the entire field. DRI staff then mosaicked images for each field together into one large data set. They then conducted an analysis of the resulting mosaic image to look at variation in plant cover and correlating plant cover to what caused variations in cover.

“I don’t know that we gave them everything that they were hoping for because the project would have required more involvement of the farm management with the DRI team,” according to Lynn Fenstermaker, Research Professor and Deputy Director Division of Earth and Ecosystem Sciences at DRI. According to Lynn, at the end of the project the farm manager, “went 180 degrees from being reticent about the project to being very excited about the products and wanting to use UAS in the future to look at every single field and determine how best to improve yield.” DRI conducted the pilot project for a subset of fields at the main farm (identified by the farm manager as high priority), which was a small subset of the entire Winnemucca Farm acreage.

The 3-D hill-slope images that revealed elevation variations within each field were seen as very valuable to the farm manager. The imagery showing percent vegetation cover right before harvest was also considered to be of high value because these images allow the manager to assess what the potential yield would have been if there would’ve been 100% cover. This type of imagery and image products are very helpful to for targeting pest management instead of blanket pesticide application across an entire field.

The pilot project did not have the time/resources to track specific metrics such as water saved, pesticides reduced etc. DRI talked to the farm manager about a variable rate irrigation application to reduce water use based on findings, but Winnemucca did not have that equipment available on the farm at that time. The type of equipment that would be needed would be specific computer software that is still under development and variable rate nozzles on every irrigation center pivot. While Winnemucca could alter the application of water on the field, they didn’t have the ability to alter at the fine level of detail that the UAS data would have recommended.

It was discovered during the course of the project that multi-rotor platforms, i.e., DJI Matrice (6-rotor) and DJI Phantom (4-rotor), provided greater stability, particularly during windy conditions. GPS integration was found to be very important for providing the best possible mosaic of individual images into a composite image for an entire field. Another conclusion from image analysis results is that the better the camera spatial resolution (i.e., higher megapixel rating) the better the mosaicked image products.

It was also determined through the testing of several different software programs that a combination of AgiSoft PhotoScan and ArcGIS software provided the best set of image processing and geospatial tools for developing the final composite image products as well as the vegetation index images that the Winnemucca Farms farm manager identified as being most beneficial for crop management.

DRI looked at different sensors and found that high spatial resolution was more important than spectral resolution, which is not what they had anticipated. They also found that with the winds that tend to come up midday in the Mojave and Great Basin deserts, using a multi-rotor platform actually worked better than a fixed-wing platform. The fixed-wing has more surface area which provides greater 3-D movement of the aircraft, which in turn, makes it more difficult to mosaic images due to the variable orientation (3-D tilt) of individual images. Whereas that multi-rotor is more stable in the wind, more level and delivers better quality imagery.

The final significant accomplishment of this project was the development of a user-friendly, web-based visualization tool that would be intuitive for farm personnel use. DRI developed the online tool using software available at the Institute, including the resulting ArcGIS image products. The webpage interface was developed using Adobe Flex integrated with ESRI?s ArcGIS Server version 10.5.1. A MicroSoft SQL Server 2012 database was used to store and host the UAS image products for Winnemucca Farms. Scalable data layers available from ESRI?s public cloud services were used for the continuous image background and infrastructure features, and the individual UAS image products were published to the site. Individual UAS image products can be viewed using drop down menus that allow farm personnel to select the image type or types they would like to view for respective fields and dates of acquisition. The website has capabilities that will allow the farm manager to zoom into high spatial resolution UAS images of each center pivot irrigation field.

Lessons Learned

A final report published by DRI and AboveGeo listed the following lessons learned from the project:

  1. It takes time to develop trust with Farm Managers given the commodities risk associated with large corporate farms. Non-disclosure or similar informal agreements to limit access to data and results to only farm employees are good first steps in gaining trust.
  2. Initially it was thought that fixed wing platforms would provide the best data given their ability to cover large areas with the least number of landings to replace or recharge batteries. Because wind is almost always an issue and the fixed wing aircrafts tested provided imagery at too many orientations for accurate georectification and mosaicking, they discovered that rotor UAS provided better quality imagery.
  3. Sensor spatial resolution is as important if not more important than spectral bands to produce the best image products.
  4. AgiSoft PhotoScan appeared to perform as well as Pix 4D software, which is a more expensive commercially available software package for processing UAS images. Web-based data processing software, such as Drone Deploy, may be a good alternative option.
  5. Image processing is the most time intensive aspect for commercial UAS businesses given the large volume of images acquired during a single UAS flight. At this time, there is not a cost effective solution available that can significantly reduce processing time, other than acquiring and/or leasing expensive parallel processing hardware and software systems or purchasing licenses for cloud-based image processing.

Further Adoption

This was a public-private partnership and DRI was partnering with AboveGeo on the project. Winnemucca expressed interest in contracting AboveGeo after the project to continue to fly UAS systems for their fields. They expressed interest in using the technology to cover all fields in the future but it has not been confirmed whether they have moved forward with this or not.

About AboveGeo

AboveGeo collects, analyzes and displays, aerial acquired, geospatial data using Unmanned Autonomous Vehicles (UAVs). AboveGeo provides services, equipment, and consulting to public and private sector customers – faster and for a fraction of the cost than can be done by existing means.

Abyss

The Issue Facing Southern Nevada Water Authority

In the efforts to maintain Southern Nevada’s precious water resources, The Southern Nevada Water Authority (SNWA) needs to conduct assessments of its major infrastructure and water intake systems to understand their condition and identify any repairs or upgrades that might be needed. Reaching and providing high quality imagery in areas such as Lake Mead can be challenging because of the depth of the intakes.

SNWA partnered with Abyss Solutions to conduct comprehensive assessments of three water intakes at Lake Mead and a standalone reservoir facility. Abyss Solutions is a robotic infrastructure assessment and management company based in Australia.

“Lake Mead and Hoover Dam are like American icons,” said Abyss Solutions company Director and COO Masood Naqshbandi. “The main challenge there is working at that depth. We were at 60 meters plus underwater. We had to customize our rig to get to those depths. We wanted to get a good understanding of the structure.”

Result of Pilot

The underwater inspection and condition assessment of the Lake Mead intakes functioned to gauge the structural integrity and extent of invasive quagga mussel growth in the intakes. Utilizing Abyss’ remotely operated vehicle controlled from a sampling vessel, the company surveyed each intake in mid-April, 2018, collecting more than 6,000 photo representations of the structures. The images were then evaluated and enhanced off site with algorithms to ensure true-color details and other finer points were visible. Three-dimensional depictions of certain faults and points of interest were also produced, while fault analysis allowed for examination of potential structural defects including corrosion, deformation and fractures within the intakes’ infrastructure. The condition of the intakes was then judged utilizing standards from the 2001 edition of the “ASCE Underwater Investigations Standard Practice Manual.”

Abyss found two out of three of the intakes to be in good condition. One of the two, which was inoperative at the time of inspection, had no visible damage though its structure had minor deterioration. No repairs were recommended, but a coating of quagga mussels at least 5/8 of an inch thick suggested a need for continuing monitoring and treatment of the region. The second “good” intake system showed a light layer of quagga mussels and apparent minor corrosion discoloration at a weld spot. Abyss suggested further investigation of the seeming damage at that spot as well as continuing quagga mussel treatment and observation.

A third intake system, which like the first is also currently out of use, was reported to be in fair condition due to apparent corrosion discoloration on screen support members. Abyss recommended repair of that problem should the intake system be put back into use, and it also suggested continuing quagga mussel assessment and treatment for this region as well, due to two or three dense layers of the invasive species across the structure.

Three-dimensional images of certain points of interest provided the water district with an even more advanced ability to assess the structure as a whole, with zoom and rotation abilities as well as clickable annotations.

The SNWA has put into effect treatments to keep the nonnative quagga mussels from colonizing its water infrastructure, and the results of Abyss’ work show those vital measures have been successful so far, said SNWA and Las Vegas Valley Water District spokesman Bronson Mack. “We’re very interested in advancing water technology for ourselves and for the water industry as a whole,” he said. “That high-fidelity imaging tells us that the system is working as it was intended.”

The technology used to assess the intakes also delved into a standalone reservoir, and a three-dimensional analysis of the system was compiled for engineers and other officials at SNWA, offering a complete portrait of the state of the structure. Through both assessments, Abyss Solutions provided the Southern Nevada agency with early access to an innovative and relatively low-cost technology. The remotely operated vehicles provide a smaller-scale alternative to massive machines with an enormous cost of operation and purchase.

Further Positive Impacts in Southern Nevada and Beyond

While in the country, the company also did a pilot with the U.S. Coast Guard, and its technology is being piloted in cooperation with oil and natural gas companies in the Middle East. It is also piloting its algorithms in the United Kingdom. Such projects will expand the knowledge base of the Abyss crews involved and allow them to better test and refine the technology they use in Nevada and abroad.

“We need water tech here,” said WaterStart Chief Executive Officer, Nathan Allen. “We have the smallest share of water in the Colorado River. We’re the driest state in the U.S. – always have been and always will be. The big benefit is that we reduce the risk of trying new things. By leveraging outside monies from the state or private interests to support pilots, our members are able to spend less money. The amount of red tape they have to navigate to try something new is reduced.”

Abyss Solutions has made Nevada its home base in the Western United States as a result of its partnership with WaterStart. It is now seeking additional work in the region in order to secure a full-time presence in Nevada. The company is in the process of discussions with the Las Vegas Valley Water District to arrange inspections of groundwater wells and reservoirs, providing a cost-effective manner of comprehensively monitoring vital water assets in the region.

About the Abyss Solutions Technology

Abyss Solutions is a robotic infrastructure assessment and management company based in Australia. Founded by a group of four academic researchers and advanced-degree students at the University of Sydney in 2014, the company offers water resource managers a detailed appraisal of the condition and environment of their underwater infrastructure with cutting-edge technology. Utilizing a remotely operated vehicle, a high-fidelity imaging system and a refined data analysis process, Abyss captures visual, acoustic and location data from the infrastructure. The company can then interpret the collected data to generate three-dimensional models of such systems, assessments of quality/condition and periodic evaluations of changes in the infrastructure over time.

http://abysssolutions.co/