Underwater Asset Management: Innovative Solutions for Ports Infrastructure Sustainability

Well, hello, everyone. Welcome, and thanks for attending. This, bright insights, thought leadership webinar, on future ready underwater asset management. For those who have attended our previous webinar webinars, We hope that you've been enjoying and learning along that journey. So my name is Andy Bolton, and I will be your host today. My role at Bradley is I am the transport and facilities lead, and very much enjoy working in the ports and marine infrastructure sector So let me just take you through the rhythm, the agenda for this webinar session. I'll cover some housekeeping initially. I'll talk about our presenters. And then we'll get into some detail about underwater assessment technology. Capital investment planning and the role of spatial technology in joining those capabilities together. And then we will finish with, panel and questions. So first of all, in terms of housekeeping, please use the icons on the bottom of your screen to ask a question. You can read the speaker bio speaker bios there. You can contact us or you can request a demo. Please send through any questions as they occur to you. Remembering that if you're thinking of a question, then probably someone else is thinking the same question and a seeking answer to questions. So don't be hesitant in raising questions as you go. If we don't get through all of the questions, we will follow-up after the webinar and a link to the recording will be sent to all of you after this session. So allow me now to introduce the team. The team itself, collective experience in asset management for over fifty years. So I'm joined today by Matt Curton, who is the CEO's road CTO of, one of our technical partners, roving intelligence. I'm joined by my colleague, Renuka Branda Wearer, who is a principal consultant in strategic asset management at Bradley. And again, one of our other technical partners, that's Esri, I'm joined by Tom Gardner, who's an industry specialist, and so it does a lot of work in the port's space. So before we get into the detail, let me just take you through the landscape of asset management life cycle, as I said, to draw together the content we are going to cover today. So if we start off with the process of asset data collection, in terms of above water, activity. It's a really well understood approach. Either, engineers walking around with iPads ticking Wiscount checklists or, more automated approaches in terms of drone technology. But what we're gonna talk about today is the role of underwater asset collection. And also associated with that, we're going to just talk a little bit about the data analysis that needs to occur once that information has been captured, including the preparation of three d image maps, or indeed maintenance task list, which we'll cover a little bit later on. Obviously, that information then needs to go somewhere. Into an asset register where you'll store not only the condition data, but performance data you're collecting from your other operation activities and the ability to trend both the condition and the performance data over time. In terms of capital investment planning, that's always a snapshot of that information from the asset register, which hopefully is your sole source of information and the capital in place in capital investment planning function produces, a a number of well understood outputs, such as long term financial plans, capital works programs, risk profiles, hopefully asset management plan content, treasury or board submissions, as well as the ability to draw all of that information together via the use of GIS and spatial technology. An optional step that some people undertake is to draw together those capital works programs that come out of the CIP function and rearrange them to give you time and place efficiencies, bundle of work together before they go to the capital projects delivery team. The PMO were who'll manage those annual works programs and, manage the delivery of those capital activities. And the piece that a lot of organizations forget to do is once those capital projects have been completed, remember to go back and update the asset register and indeed start that whole workflow again in terms of collecting new data. The idea here is that you cycle through this workflow and your capital investment planning models get more, get deeper in nature. They drive, more confidence. You'll expand your asset register as you seek more data to help with that decision making. And it's just an iterative cycle that you'll carry on completing over time. I'll just describe the types of organization that gets involved in each stage, starting off with, the data collection. Well, typically, you see that undertaken by specialist survey companies. You've then got the data analysis or the transformation where you clearly need some engineering capability to perform that work and then you've got your asset registered providers. I just call these the bunch. So we all know who these are. You've got the dominance of the confirms sorry, the the, the main aximos, the technology ones, the oracles, and indeed the brightly portfolio as well. When you get into the capital investment planning, that's again where you see the specialist roles emerging to perform to bring that, you know, detailed expertise to to those conversations and, indeed, work with those specialist GIS providers as well. So why are we talking about this today, why are we looking at that landscape? You know, why is this important for the Port summary in sector? So here at Brytely, we have many, many years, of working with infrastructure, operators, infrastructure maintainers across many, many sectors. And it's fair to say that within the ports and marine structure, we the level of asset management maturity, maybe lagging to some degree behind those other sectors So in a, an attempt to raise the levels of maturity, we always like to explain to our asset management colleagues what's going on elsewhere and how can that technology be used better within the ports and marine space. You know, within the port sector, you see certain ports leading for a while and then dropping away is very much an ebb and a flow, type of ribbon we see in the port space, typically driven by the personalities at that point in time within a port. But one of the key triggers to do this better right now is the emergence and the acceptance, the adoption of the Wiscam assessment method by ports Australia. So you've now got a method to capture both above ground and below water, asset information in a standardized format. You capture that data, but then how are you gonna add value to that data you've captured and you put into your asset register? And that's what we're gonna talk about to some degree today. So, the rhythm of a session is gonna be looking at the data collection techniques for underwater activity looking at the capital investment program capability and also looking at GIS visualization capability, recognizing that from a lot of ports, the GIS spatial capability has been very siloed. So it's a great opportunity to make more use and better use of that GS capability, across the other functions within the port's asset and engineering management team. So the key focus areas I'm going to move on to will we'll we'll, look at this underwater technology. We'll look at the capital investment planning function, and I'll I'll be calling that the CIP function. And then we'll touch on the spatial capability and how that can be used better across the ports sector. So without further ado, I'll bring in my colleague Matt Kirkman from roaming intelligence. And we're gonna have a few questions about the underwater technology and how that can be used in terms of collecting asset data. But before I start talking to Matt, I'm just going to show you a short video that demonstrates the underwater technology we're going to be covering. I'm Matthew Curton, the Sea of roving intelligence. Roving intelligence is a organization that utilizes homegrown technology to deliver services in the submerged infrastructure inspection space. In theory, we can look at anything that's underwater, any sort of merged asset, or environment. So anything from piles to sheep pile walls, or we can go in and we can do a search and recover of anything that's fallen overboard or offshore or anything like that. Our approach is to do a complete survey of every surface area of submerged materials and enables the customer to make far more educated decisions. The technology is forever improving, so we're always into the latest and greatest things that we can into our products. We can have, multiple types of cameras on, on the road at the same time scanning devices like the sonar, and all the results that we get out of those, we're gonna keep, and we can analyze in ways. So we can be able to supply a service that people can rely on. One of the unique attributes of Raven Intelligence is the way they were able to accurately pinpoint she'll referencing an area on a pile, a sheep pile wall, a pile on, a defect that can be then observed year on, year on. So welcome, Matt. What I'd like to do now is let's talk about the technology. And the first question I've got for you is, you know, tell me what is happening in the underwater technology space, where has it come from and where is it going? Okay. Thanks, Andy. Thanks for the intro. Yes, certainly, the the world of asset and utilizing submerged robotic technologies moving very quickly at the moment. And I'll talk very briefly about the slides you can all see on the screen. In a moment. In the past three years or thereabouts, support for, asset inspections amongst ports, marinas, as well as many other industries move beyond the traditional, divers collecting basic basic image sets, notes around asset condition, etcetera, and move quickly to capture more fleet datasets, demonstrating value that will help mature the current processes. From what, in a lot of cases, is is a level one out of five, to more respectable levels of, value chain maturity. Not only are we able to get more work done using these sorts of techniques and technologies, but the value of the data that we collect and the collection process has significantly increased over that time. Most of that comes about, and I'll talk more about that value in just a moment, about the unique way that we capture artifacts around the condition of materials that form a particular asset. And you can see on the screen there that, this is some of the payloads that we carry on the ROV at any particular dive, a lot of those, surrounded in navigational capability. So as we've got very accurate, very reliable geospatial data collected with every image every sonar scan or every sample we take, in the form of thickness tests, cathodic protection tests, etcetera, etcetera, A lot of that value, also, as I said, consists of, very accurate spatial reference data. We also have a a vastly reduced OH and S risk as compared to putting people in the water to to conduct these sorts of inspection work. We can typically spend more time on the actual inspection on any particular given day. We can certainly put the ROV in the water whilst there's ships alongside WARves etcetera, in a lot of cases where they won't, or harbor masters won't let divers in the water. And our time to actually deploy this rove technology and recover be back in our van and and be disappearing is is around about fifteen minutes each in the day. So very, very quickly to deploy. In addition to this, the basic inspection capabilities, all of our dives collect additional value added data, just in normal course of the operation, including, under wolf bathymetric data, which is quite useful for looking at the movement of sediment and so forth around the environment, the typical artifacts associated with water column protests Excuse me. Water column profiling. And in case of seabed and birthing Basin surveys that we do quite regularly, our AI engine also identifies invasive fish species. And we're able to do counts of those particular incidences, and help build up trend analysis data and a whole heap of other fronts above and beyond the condition assessment data. Because of the robotic nature and because the integration of all of those sensors that you're seeing on the screen. We've got a greater ability to navigate and operate in poor visibility conditions. High current environments. The ropes capable of standing still all by itself and holding station and any anything from four knots up which is quite difficult for a diver in the water. And we incorporate as I said before. We fuse a lot of sensor data to give us very accurate navigational, information. All of those, assessment data, including the HD images or geospatially referenced, all the data is immediately available for cataloging into asset registers, plus an asset management systems and GIS systems. From this, the build up as we frequently revisit a site based on the inspection cycles gives us the ability to create accurate trend analysis through the comparison of imagery. And, it removes a lot of subjectivity. In that process. I'll talk more about AI in just a second. And one of the other advantages, which our engineers or our customer representatives actually quite enjoy is we can stream any of our missions from the robotic solution in real time back to an engineer's desk or in in fact presented on a screen, above water whilst we're conducting the operation. So engineering resources at a customer site can direct, the operation to some extent. A lot of times when divers go in the water, the only artifact the customer will see some still imagery, and maybe some go imagery and so forth. So in short, the ability to provide the customer more accurate real time data that will help them with maintenance decision in spend, and finally move, this this sector into the twenty first century. Thanks, Matt. Now within the capital investment planning fund we love component level data. You know, we're that that's what gets us excited. Can you just cover the ability to capture that component level data for me, please? Sure. Look, what what you're seeing on the screen, a lot of our audience today will be reasonably familiar with. It's a traditional, wiscam Excel spreadsheet that we would utilize for scoring the, material condition of assets and sub assets. We still produce these traditional artifacts. But we also produce an interface file in any format needs to be digested into, you know, management and decision making platforms. We, pride ourselves on being able to be very thorough in our data collection. So reporting on underwater assets can now be done such inaccuracy and such a granularity that all sub components can be assessed to present a more complete picture, of the asset than's ever been present before. We don't just do a simple swim through. We we do literally go past or up and down or across every sub asset that makes up that structure. Additionally, and this is this is one of the means we're able to do that, utilizing, artificial intelligence technology and also repeatedly doing these inspections, over the maintenance cycle, we can assess miss material changes in the asset. And therefore, a more accurate rate of deterioration can be built very, very quickly. It it would be nice to be able to more confidently and reliably pick when an asset is really going to fail or when maintenance money is really need to be spent on assets. And this is really what this process is all about. And our vision for producing these these technologies and capabilities. Because, yeah, at the end of the day, the less we spend on staying on top of maintenance, we might, we might not need to spend the more customer has, the high value, high return capital in projects. Thanks, Matt. Now you mentioned the role of data analytics and and AI Can you just expand on that for me, please? Sure. The the image you're seeing there is a a very, very brief mapshot or or sample of, AI engine we already used post dive at the moment. The reason I say post dive is that we're building a real time engine that will reside on the ROV, that will do this, literally in real time. As everyone's aware, data analytics, using AI is, progressing very quickly on a in a whole heap of different industries, and anything that speeds up and provides more accurate reporting on the value or otherwise of of any product or service is where much of the future money will be spent. Port assets are no different and technology to help. That is moving forward very very quickly. And we like we like to think that we're, one of the leaders in that space, collecting more accurate real time data that help port owners better direct their spend will will become, a talking point, around many boardroom tail as you would expect. Before long, it will help reduce insurance premiums potentially, as the data help us with more accurate risk assessments including the reliable and accurate baseline from which further surveys will be compared. AI developments not only automate and improve our accuracy and remove the subjectiveness of of material condition assessments, they can be extended to many other data capture and analytical activities. These, but but certainly not limited to, these include the assessment of environmental biosecurity hazard identification. And as I mentioned before, the assessment of invasive species. And looking at that, image on the screen. Now what you're seeing is our AI AI engine, picking up not only the fact that the, artifacts covered in biofouling is quite typical. But that is another measure of environmental health, particularly when we use it to, produce trend analysis but more importantly on this image, we're seeing it in real time pick up the corrosion and the certainty and degree of corrosion on, in this case, a a metal sheet firewall So we can very accurately with a combination of our navigational information and data and our AI analytic go back to the exact same spot within a matter of millimeters. Fourteen to twenty odd millimeters. That's how accurate. And check that same spot in a year's time or two years time to be able to build up that trend analysis data. Fantastic. Thanks, Matt. Matt, so we've covered component level data capture. We've talked about referencing the WOSCOM assessment protocol. Can you explain to me the role you can play in providing the maintenance team at an operational level you know, with defect lists, with maintenance lists, whatever you wanna call them in that space. So, you know, how how do you go about what what what can you deliver there in terms of defect capture? Okay. So as you probably appreciate, it is a very reactive process at present. Within Australia and further afoot, there's a lot of aging assets, peers, wharfs, and and so forth. And, there's been a hesitation, in the past in how much data that they collect around that asset. And in some cases, there's been many, many years, decades, If not centuries where ports haven't actually done a detailed inspection of a particular asset to determine its actual condition or and more importantly, what sort of lifespan they might be able to, expect out of that asset moving forward. A combination of this this aging assets, very little condition related data. And in some cases, no data. Many ports and even count souls, for inland waterways and so forth. Very little insight into the true condition of those assets, and its remaining life. And maintenance here or remediation spend. So that's what this is all about. While this has had some traditionally, as I said before, we used divers, divers will take individual imageries in some cases, video. They'll take a whole heap of notes around, spot checking certain piles within Warf structure, etcetera. And then all of that will then get distilled up into a WISGAM condition reference data. Heat map. What we do is we we look at every single one of those sub assets and build a very complete and very accurate data set to give you a lot more insight around that state of condition and and as I said before, a better appreciation about deterioration trends which ultimately, worst case scenario, can lead to the prediction of, potential failures and so forth. Yeah. Look, I guess that's really sort of summarizing the case for for utilizing a far more autonomous in some cases, but certainly automated and very, very efficient underwater inspection process. I'll park you there for the time being and, we'll come back to you with some more questions. What I'm gonna do now is take everyone through the workflow. We've we've done our underwater condition assessment using this drone technology. It's the data's now sitting in in your asset register. You're running some trend analysis. You can see your data there. And let's talk about now that you the jump from the asset register to start taking that data and start to do your capital investment planning. So I invite my colleague, Renuka, to to join me. And Renuka, my my first question for you, and we hear this a lot in the space is that, many organizations, many agencies, they defer, they park their decision to go and undertake their capital investment planning because they're busy implementing their asset register in the maintenance management system or they they wanna get all of their asset classes, you know, migrated to that form, in your opinion, Renuka, when should people really start the capital investment planning processed. So they have to wait until the system is perfect. Tell me about that. Yeah. Thank you, Andy. And my answer is, no, they don't have to wait until a corporate system is in place. It's relatively easy to start building a capital investment plan early on. And in my opinion, every organization should start doing so. Let's start with the basics. Developing a capital investment plan means taking a call of life approach to your asset base. And the life cycle models with active scenarios informs capital investment plan. The basic information required to build a life cycle models are as a age or condition. As a useful lives and as a replacement value or treatment cost. The beauty of life cycle modeling tool like predator is it is not tied to any enterprise system. So we can get a snapshot of current data from any system and if necessary can merge that data with any disparate data sources. So it's just getting that data. And, collecting in a Excel spreadsheet. And it provides, they can always use industry benchmarks. And once the organization get a hang of building life cycle models, they get to understand other information relevant to organization, no specific cassette base that will they can use to build more robust and sophisticated models. Also, it can help with structuring of as a registered data. And when it says, okay, How do I structure by corporate as a register? Whether we how do we make high level grouping of functional locations? And, how do I need to componentize my assets? How do we record maintenance data? So in actual, by starting to build a capital industry and plan early, give opportunity for organizations to understand the data gaps focus on collecting value add data and can help with as a register structure. Thank you. So what I'd like to do now is move on and talk about the handover of the data from Matt's team at Raleigh Intelligence. And then what you do with that data, you know, it it arrives on your desk. Can you explain to me, you know, the process you then go through to end up with some capital investment plans? Yeah. Certainly. We have closely worked with Robin intelligence, so they provide us with asset condition data that's in line with, we scan and in a ready to upload format, as Matt mentioned, to incorporate as a registered, you can you can use it in life cycle planning models. But if I speak more generally, There's a basic workflow that we have adopted from years of experience, in building life cycle models with many organizations. First, it's not only the other condition data. We ask for all, like, asset in other asset information. From the organizations if they are not using our corporate system. And we also request for additional information such as asset management plans, long term financial plans, service level frameworks, and risk frameworks from the organization if they are available. And once we have this information, we perform a basic, data review and a gap analysis. And if there are sufficient data, we can go and build on the first cut model as well. If not, we get back to data and have a chat with the organization on what we need to do about data. And the next step is we sit down with the subject matters experts of the organization to discuss organization, service level framework. And we look at the treatments the organization performed on their specific asset base. And also we discuss, the treatment, intervention levels of assets. And while also when we do that we also look at the, okay, but are the treatments that's performed by the other organization on this specific that this organization that can And if there are any missing data, we can go and fill that data with industry benchmark. We can utilize, for example, the degradation profiles, given in this term manual or the useful life, defined there. And then we would go and look at going to build what if modeling scenarios. There are two basic scenarios we look at. And first one is what is the funding requirement to maintain the asset base as per organization service level standards? And this one is what is the service level we can achieve with the current funding allocation as per our as per the organization loan term financial plan. So it tells us actually what the future of further asset base look like if we can spending as the current strategy. And then the last step I would say in a building a basic model is the model calibration, which is very important step sometimes forgotten is to actually where we ask organizations to go and do a free verification of modeling outputs. And from their own words, it's a matter of fine tuning the models build different scenarios, etcetera. So that explains what we do with data we get. Thank you, Enrique. That's very good. So in my opinion, and and just understanding where the general asset management market places. In today's asset management landscape, it's no longer good enough just to use condition data. As your single driver for your capital investment plans. Let's step away. And can we just talk about, you know, how do you add debt how do you add integrity, and and and greater confidence into these models? What other pieces of data do you look for? You are very right, Andy. So condition is just one performance factor and not the only one that influence renewal replacement decision making. So other factors such as capacity, utilization, functionality also drives the type of treatments carried out and reflect more real world decision making. And if we can get this information. We can certainly include them in the model and which will be a real value add. And we also look to, incorporate the asset information such as the material type or, the location of the asset whether it's on show asset, off show asset, under boat asset, buried assets, etcetera. And, because they can drive the they have a significant impact on asset light cycles or as a unit cost of, renewals. So, but there's another one that's quite important, which is the, organization risk profile. How do we deal with that? Every organization struggle with available funding to do the work. So we need to focus minimizing organization risk profile for the planned, capital investment scenario. For this, we integrate with organization risk framework and use asset consequences of failure or criticality in modeling together with as a condition or performance factors to create a dynamic risk rating which we used in modeling to prioritize asset. So then in when we do the scenario modeling, So we it will be a balance. They can organization can select which scenario provide the acceptable balance of cost, performance, and risk. So these are the key factors we can strengthen the model. Thank you. What I'd like to do now is just very briefly talk about the common challenges you see every you come across every day and working with your client base. You know, what are the common mistakes people make or where where are the gaps? You know, what do you find in your everyday, capital investment planning world? Okay. Sometimes we see like, a lot of organizations wait until they have a perfect data set to start modeling, but my advice is don't wait because you will never get a perfect data set. So start simple and start with what you have made assumptions. And then the other challenges actually for many organizations, data using excel spreadsheets in many places of the organization in different departments. So collecting them become a challenge, and the biggest challenge is find a unique parameter, but we call it asset ID in all of these, spreadsheets. So that's actually take us try creating a single source of truth. So you have those, you can actually collect all this information. Together. And then there was another one, what we see is initially there might be a lack of executive by but we have what we have seen is as we go on and when they see the value add it bring to the organization, you can there's actually quite a buy in and then appetite for the improvement of capital investment investment plans from executive pointing. And last but misplaced is the problem with the data, like the skills, knowledge, and capability of the staff in all that's, yeah, that's also very prevalent in the industry. Thank you. So we've talked about some complexity around capital investment planning, and I'm sure our listener is is thinking know, this sounds like a lot of work. So in your opinion, what's the typical time frame it takes to, to stand up these capital investment programs. And and what's the demand on the agency themselves in terms of their contribution they have to make to getting these plans up and running? Well, I would say that it depends on, what type of asset class we are modeling and but the out put requirement and also the data quality. But, like, it might take some between three to four weeks to, yeah, a couple of months, asset class. And in terms of commitment from the organization, station staff as subject matter experts. I would say about two to three person days per asset class. And this is for providing guidance on organizational service frameworks, risk framework, treatment practices and also for model calibration which include the field, testing of modeling outputs. Thank thank you, Renuka. Allow me now to bring in, our third presenter. This is Tom Gardner from Esri, very strong partner of, of of of Brytely. So Tom, what we'll do now, let's just explore the value of JS and how we can really use the power of JS to to to bring this whole process to life. So we've gone from initial data capture underwater. We've gone through the analytics function around capital investment planning. And let's now move on to talk about how the GIS, the spatial capability can be better used. So my first question to you, Tom, is you know, why is location important for ports? Can can you pick up on that, please? Thanks, Sandy. It's an interesting question, and really it's, I guess ports are inherently, low focused. If you have a look at the actual, any port around the country, there's, significant amounts of, operations and functions that are all a lot of moving parts. Now, I guess, as we've seen from Matt and Renuka's presentation that accurate capture of assets, and asset condition are critical in that whole life cycle analysis perspective. And that location, component really brings together a better understanding and viewing of of of what's going on from an management perspective. That previous slide that, Ranuka showed really gives a, an overall view of, to a broader audience, at their standing of, in that instance, options that can be made and used, and decided on in that space. From my perspective, I guess, if we're looking at GIS, many people talk about the fact that a picture is worth a thousand words, I'd argue that a GIS is worth a thousand spreadsheets. It helps transform that tabular information into kind of a visual representation of what's going on. And if we look at it from a ports perspective, the operational function of a port. We have, location based functions tied in with vessel management and tracking, birthing, transportation and logistics, the whole asset management maintenance, and workforce management side of things, as well as security. I added on to that, we'd probably look at a lot of use of GIS in planning and land use management and lease management at a port, as well as environmental management, and even strategic planning and development. And a lot of this actually then needs to be brought back together and communicated successfully to different, people within the report, and sometimes the broader stakeholder and community from the community engagement and using location a visual tool that, is really a much greater provides greater understanding for most people. So, Thomas, let's go from that broad view, if you will, to to maybe a a focus view. And can you explain how JS can help within the asset management function if I put it that way? I guess it's interesting, to see, the current time, speaking to ports across the country, a very large number of them are either implementing new asset management systems upgrading their asset management systems or looking at getting better value out of them. So there's a lot of activity around that space, and I'm not sure if it's just tied in with the fact that we've got critical infrastructure that needs to be maintained and number of the assets are starting to get to, the end of their potential life cycle, which has been a part of that driver. But I guess GIS plays a really key role in supporting that whole asset management and asset management systems by actually integrating the location and the asset, identifiers, condition, and other information to provide a higher level of operational awareness of of what's happening where on the port from an, an asset management position, condition. It also provides a, bringing GIS and location into your and management system enables you to really maximize the investment in your asset management programs. So looking at better scheduling, not only of maintenance programs, but understanding how those, schedules of maintenance work can actually be aggregated together on a locational basis to, look at if there are potential shutdowns, or or birthing changes, to to part of part of the actual report. Other work can be done at the same time. So providing that kind of geographical advantage. It also enables using the GIS as a a location of record for the asset registry. You have the effect of the asset management, system having the system of for the asset information, and then the GIS provides that locational record, of what's actually used together. Quite often we see the GIS as well as almost a front window or a front end to asset management systems for the non expert users. Quite often presenting that information to a broader audience, within the port so they can understand what what's happening where without having to go and speak to an expert or use an but system to get that information out. Fantastic. That that last point certainly resonates with me. We have many of our customers using every story maps just to tell tell that story to to a wider broader audience. So so final question, before we go back to the the the the the group questions is what role Tom can spatial analytics play in supporting decision making. Oh, I guess number one, GS is more than just a visualization tool. A surprising number of our customers is not using a lot of the power and the and the analytical power that GIS has and brings to it. Using GIS, we can actually start analyzing patterns of activity understanding what's happening where, or actually predicting what may have happened in a certain location, and also understanding, ways of, reducing risk in areas by actually analyzing kind of our potential health and safety issues around, incursions of, risky vehicles with locations of staff or people that are working. We can start using the GIS from an analysis perspective to analyze traffic patterns, to understand if there are actual bottlenecks. We see this actually in the resources sector a lot of looking at, track, movements, and so on to understand if they're actually bottlenecks and delays, around areas of the port. Mapping and analyzing health and safety incidents to see if there are actually patterns occurring over a period of time. Ports are also starting to deal and manage with their own utilities that they have. So we we are in discussions around looking at managing communication networks and fiber and water networks to understand what's happening where because a port is really a small city which needs to be managed So, analyzing that, and using locations is a critical component. From a security perspective, we we start tapping into and using, GIS to look at security cam camera coverage or where would be the best place to locate a security camera? But also looking at actual, information related to access who's in what area should they be in that area, and do they have the right approvals and those sorts of things? So looking at that, that whole, space is quite interesting. From a, environmental management and a risk management perspective, quite often modeling spills and flu in case there are incidents, and even from an emergency response, we're seeing GIS use, to provide that analysis and that capability. And now with the advent of a lot, of, ports kind of picking up their own drones. We're actually seeing a lot of drone imagery being used to capture, stockpiles and regular kind of analysis on stockpiles and actually creating thirty meshes and data kind of, representations of their port. And quite a lot, quite often a lot of that information is actually brought together or is being brought together to generate a Freddie representation of their port including all the asset elements to create an actual digital twin. And we've got a couple of ports, you know, call out Southern ports as one of them. We've seen some amazing work done around that whole digital twin, in the three d space happening. And it goes on beyond just the actual birth line into, dealing with the actual bathometric data and managing that, as well as, bringing in obviously AIS information and working more in that ports operations space. So it goes on and on to a degree. Thanks, Tom. Yeah. You've given us a thank you for a really broad view of how to better use the spatial capabilities. So allow me now just to summarize the conversations we've had today. So what we've talked about is being you know, that condition data capture, and flowing through to the corporate asset management information system. It also could be handling your accounting. It could be handling your maintenance management. And then you've got your, capital investment planning function. It's also called life cycle modeling. It's also called asset investment planning to produce those scenarios to generate those long term financial plans to generate those capital works program trip, but they're all very much, engineering asset authored and and and there's a lot of complex detail detail in those. And I think one of the key things we have to do as an asset management community is we have to become better storytellers. So we can take the consequences of that complex engineering stuff and presenting it in such a way that the grown ups really do understand the sequences of their decision making. And that's where we really see in our space the value, you know, all there's three of those spatial packages to take complex, the complex that outcomes and present them in a language that's easily understood by all. So that's kind of our world. And, of course, it ends with that, project delivery. And don't forget the fact that the project's activities need to then go and update the asset management system and the life cycle of data capture starts again. So I hope that was useful. Let's move on now to taking some of the questions that have been raised through the session. So without further ado, I see that we have some questions, and and and Matt's I hope you're ready. So I'll just take these. So the first question is from David C. Can you take steel thickness readings with pile jackets in place. Yes. Is the short answer? We've got a number of different ultrasonic thickness testing type technique. And tools. A number of those specialized, for below water as well as above water thickness testing. That's slightly different instruments. But to answer your question, yes, we can measure, directly through pile jackets where jackets are anywhere up to twenty millimeters and us, which which in our experience pretty much covers everything that we've ever come across. Thank you. So again, David c asks, do you get three hundred and sixty degree readings from one position? Or do you need to travel around the pile circumference? Yeah. Look, there's there's many different styles of inspection activity based on what the customer needs actually are. So there's no real simple way to answer it aside from saying, if you want a very, very detailed view of a single pile or or group of piles, to get that three hundred and sixty degree coverage, at that detail, yes, we would have to make a number of passes. Typically around par, we would do three passes, top to bottom, and back again, obviously. But if we're doing and this also, relates to another question, answered by somebody else on the on the call today. Depends a lot on the level of visibility that we have. If we've got reasonably good visibility, so we can see, for example, the piles across two different pile bents or or rows of piles. We can run multiple cameras on the ROV and do fairly basic swim throughs amongst, you know, sometimes through a day, hundreds of piles, and capture all sides of those piles during those, those pile vent to swim through. So I guess the the best way to answer that is it it depends on what you need If it's a simple swim through type of arrangement, yes, we can get all pile surfaces or facets very, very quickly. If there's a very detailed analysis that needs to be done at the pile level. We will need to go up and down the pile a number of times to capture, that pile completely. And it and it surfaces. Thanks, Matt. And another question. Sorry. We we do that very quickly. We we typically traverse a pile about a meter second. So the capture speed is very, very quick. And if somebody such as an engineer, resource needs to do detailed analysis, they can show slow that footage down and do a a more close-up inspection. Thank you. Question from Darren here. How do you remove the biofouling stroke growth on elements to get clear visibility of the elements. For example, to assess carotid areas or identify poor condition of substrate. Yep. Very, very important question. So, we've got facilities, in short, they're, pressure washing type arrangement the ROV gets fitted with. We we don't set out to completely clean a a whole pile of such. But what we do after a a general swim through, we will then pick a percentage of piles. So say ten percent or twenty percent of piles within that pile structure will do that detailed up and down to to capture the full pile as I talked about for our David's question beforehand. And then at various intervals along that pile, we use this pressure washing arrangement where we can go up and clean a patch of the pile to allow us to do a detailed visual inspection of the underlying material, whether it be concrete timber or steel. Or or any other material for that matter. And that also allows us to do, very, accurate, cathodic protection, potential testing, obviously, of steel componentry, and also ultrasonic fitness testing, as well as that that that visual inspection work. And there's we haven't been stopped by any level of fouling to date. And we've come across some very, very, very hard baked in barnacles oysters and so forth. We can remove those if required. If it's a timber pile, we tend to dial back the pressures that are involved. So we can run it anywhere up to four thousand psi, for timbers and and softer materials would would dial it right back to about a thousand psi and go at it very, very gently. So I was not to undermine the, original material structure. Excellent. Now you've covered this already, but just a another brief answer, if you wouldn't mind. Riley asks How does water visibility from sediment affect data capture? Yep. Okay. So there's two aspects probably to that question. One's one of navigation. So being able to swim through a complex structure with lots of piles, rakers, cross braces and so forth. We use a mix as I touch on beforehand of accelerometers, gyros, magnetometers, GPS when we're on the surface, doppler velocity log when we dive beneath the water surface, and most importantly, Sona, technology. So, we can operate in absolute darkness with absolutely almost zero visibility certainly zero visibility to accurately navigate to a specific spot, on a on a piece of infrastructure, as I said before, to to within about twenty millimeters. Then the second part of that question is is obviously, well, if visibility is very, very poor, what sort of a look at the asset are we gonna get with our camera technology? The cameras are, a very low light sensitive camera technology, we can go right up to within centimeters of the of the structure and focus in on that and still get quite good video imagery or still imagery, enough for engineering assessment to be carried out. And that's that's anything down to three, four hundred millimeters of, of visibility. Thank you. There's another question on Marine growth. I think you've answered that one. There's a question on costing, and we'll come back to Kazin directly on that one offline. Another question for you, Matt. With survey, can you quantify by volume of sediments? I hope you understand that one because I Yeah. I think I understand the question. So, another not so straightforward one to answer. There's a whole host of different sonar tech technologies that can be brought to bear on these sorts of problems, if we're talking about a traditional bathymetri survey where we have a something similar to a a single b echo sounder. For example, we use that technology on some of our roads and our unmanned surface vehicles, to do spot, depth checks at pre agreed frequencies. What I mean by that is, we can we can run swim lanes, to any degree of, of, granularity. Anything from one meter to ten meters, depending on what you need. Likewise, along the swim lane, we can run different frequencies and take ten spot checks every meter or a hundred spot checks every meter. Once again, what sort of whatever granularity you need. All of that data is geospatial reference so it can be brought into a three d model where volmetric type information can be then calculated. I assume that's the the answer that we're we're looking for with the with that question. If not, please, happy to take it offline and talk in more detail about techniques to do that. And Tamara, you've answered this one, but Tamara also says does the ROV capture, bathymetric, as well? It does. So, these are one of the things that we just one of the many data elements that we just captured by default. Lost we're submerged, we have pressure depth. We also have altimeters. So we're we're shooting a number of sonar beams to the sea bed. Our calculations once that data's cleansed and processed or or part of that cleansing and and processing process is to understand, our tide, understand our, pressure depth. So how far we are under the, the the water surface and our altimetry. So the distance between the bottom of the road and the seabed, and consequently, we build up a a bathymetric survey profile even as we just continue to perform our inspection work under that Warf structure or anywhere else we might be. For example, one of the things we get called to do from time to time is to do birthing basin type inspections. Not necessarily one that's run from the vessel to, you know, a survey grade sort of, status. But nevertheless looking for navigation hazards and and issues that might, become a problem for shipping and so forth. Jeff through that process of sonar scanning, and visual inspection of the seabed, we we capture a a very detailed picture. Around bathymetric, bathymetric data. Thanks, Matt. So look, I can see more questions there. So, Nick, we will come back to you on your question. We're about to, to to lose the session. So, let me thank you all for attending today. I've got some email addresses here. Should you want to carry on the conversation? Just scribble those down quickly, but we will be sending you, a link to the recording. And, obviously, if you have any other questions, please, send through those questions. And for those questions, we haven't answered, we will come back to you. So Please keep an eye on your inbox for future webinars. I thank you for your attendance, and I thank my panel today. Have a good day. Thank you. Thank you.