Location: Saudi Arabia
ZEB Scanner: ZEB Horizon
Scan time: 15 minutes
This data was processed in GeoSLAM Connect and the volume of the stockpile was calculated (15,000 tons) in GeoSLAM Volumes.
Would you like to see a specific dataset that’s not on this page? Contact [email protected]
Last Updated on 25th October 2022 Scanning the Mutrah Souk in Muscat,… Read More »Scanning the Mutrah Souk in Muscat
Cape Town, South Africa
8 Hours Total
Approx. 117,000 m2
Power Station
Surveying
All over the globe, countries are looking to nuclear and hydro renewables, not only to provide their electricity needs but to meet climate goals. This is resulting in the shutting down of coal-fossil power plants that no longer have a role to play in a fast-changing world.
Opened in 1962, the Athlone Power Station was the last coal-fired power station operating in Cape Town, South Africa when it stopped generating power in 2003. The iconic cooling towers, which were known by locals as “The two ladies of Athlone” and had long been a feature of the Cape Town landscape, were demolished several years later.
The efficient user-friendly GeoSLAM equipment enabled the team to safely and comprehensively survey this hazardous and complex plant.
Proper planning was essential as demolition can be potentially hazardous for the safety of personnel due to the plant’s age-structure, and onsite teams often having to operate across split levels, in total darkness. The removal of contaminated waste can be equally challenging. Cost is also a major factor and companies responsible for shutting down plant are continuously looking at ways to be cost effective while providing a reliable, fast and efficient service.
Aurecon, a global engineering, design and advisory company, won the tender from the City of Cape Town to project manage the site for the final stage of decommission. This involved surveying the plant whilst stripping, clearing and removing unused material, redundant equipment and certain historical structures. Their task also included securing all remaining structures, leaving the site in a secure state and registering servitudes for remaining bulk services. Aurecon found Athlone to be a challenging project due to accessibility issues and lack of light. Also, because of the Power Station’s historical importance, salvaging certain unique equipment had to be considered. The team needed a simple and effective solution that could accurately map the site quickly while keeping them safe in a tough environment.
Aurecon chose to work with mobile LiDAR scanners so that the historians, structural engineers and environmentalists could have the data they needed, without having to enter the potentially dangerous site. For the Athlone project, GeoSLAM’s ZEB Revo RT scanner and ZEB Pano camera were used, as well as the ZEB Horizon and ZEB Cam. The building’s interior and exterior were scanned with the ZEB scanners The two data sets were merged to provide a full 3D point cloud of the entire building.
Using the Pano, the team generated photos that were incorporated inside the point cloud, so that the offsite survey team could have greater visualisation of the site to feedback commentary. The efficiency of the scanners and speed of capture meant that unlike other scanning methods, the team could repeatedly capture the site. This meant that decisions and assessments could be taken frequently, without the need for lots of people to visit the dangerous site.
In total, the whole facility was scanned in three days with data sets processed overnight, a total of eight hours. The combined datasets were available within a week, which enabled Aurecon’s modellers to commence work on the classification of components in the power station.
The final 3D point cloud representation of the interior of the power station enabled the engineering team to assess and quantify the amount of salvage and scrapped material to be removed from the site, and to plan the logistics of the removal in context with the physical shape and size of the existing building.
The accurate 3D model equipped the stakeholders with information that allowed them to safely and precisely analyse for activities such as material quantification, condition assessment and the preparation of decommissioning method statements.
If you’d like to learn more about how GeoSLAM solutions can help you, submit the form below.
Egypt
17 minutes per scan
82,823 m2
Construction and demolition waste
Construction
ZEB Revo RT | Housing and Building National Research Centre
The government of Egypt (GoE) are leading several initiatives to reuse and recycle the ever-increasing quantities of construction and demolition Waste (CDW) around the country. These initiatives include a national strategy and action plan to effectively manage around 40 million tons of CDW generated annually. They target to recycle 50% of CDW materials by 2030. One of the major challenges facing Municipalities in Egypt is calculating the amount of CDW accumulated, due to illegal dumping of waste being common place in cities.
Commissioned by the Ministry of Environment and the GIZ institution, HBRC (Housing and Building National Research Centre) have been tasked with finding effective methods for quantifying and characterising the amount of CDW in four Egyptian Governorates (Gharbia, Kafr-El-Sheikh, Assuit and Qena).
This project paves the way to developing an optimal construction and demolition waste management strategy in Egypt. The research team used GeoSLAM’s ZEB Revo RT SLAM laser scanner to map the construction waste piles. The scan data is a sound method for quantifying waste volumes over a period of time, due to the ease of capture and accurate data.
The traditional surveying of CDW accumulations was not practical as CDW locations are difficult to walk through and experience rapid changes to the waste quantities.
The ZEB Revo RT is ideal for rapid data capture in real time, making it the perfect tool for this job. By walking through the construction and demolition waste sites, the team are mapping as they go, shortening the amount of time spent in a hazardous environment, reducing health and safety risks.
The simplicity of the solution means that anybody can capture the data, with minimal training, making the scans repeatable as often as needed. Covering an area of 84,823 m2, the research team conducted 12 scans, dividing the route into zones and each scan lasted an average of 17 minutes.
Once the scanning was complete, they opened the data in GeoSLAM Hub where the point cloud can be viewed and prepared for GeoSLAM Volumes. Using GeoSLAM Volumes, the researchers could accurately calculate the quantity of construction and demolition waste. The findings were reported back in a presentation during the third International conference on Smart Cities.
This way of calculating volumes is fast, efficient, cost effective, safer than other methods and repeatable, making the SLAM scanner the right tool for the job. The research effort opens the door into the utilisation of 3D modelling of construction waste management sites.
The application of laser technology would enable the quick and accurate estimation and modeling of waste quantities.
If you’d like to learn more about how GeoSLAM solutions can help you, submit the form below.
Industry
Conservation
Time
48 hours
Location
Various,
Israel
Size
Three sites
across Israel
Scanned
Historic Sites
Oxford Archaeology | Words by Jamie Quartermaine
“48 hours to scan three historic sites in Israel – ambitious or impossible? Equipped with a handheld 3D mapping device from GeoSLAM, we were determined to find out. Our first stop was the Schneller building in Jerusalem. In its 160 year history it has been used as an orphanage, barracks and ammunition arsenal. A few years ago, an archaeological team unearthed the remains of a Roman bath house and winery underneath the site. The next stage of the building’s history is a conversion into a museum of Judaism – hence the requirement for a complete, high-accuracy survey of the site.
Made up of four floors, 130 rooms, an outer courtyard and a number of stables, we needed to work quickly to scan the entire site. Using the handheld ‘go-anywhere’ ZEB Revo, in three – 30 minute scans he captured the entire building, including survey control points to georeference the data. Using traditional scanners, this would have taken several weeks and involved multiple set-ups.
“With the ZEB Revo, what use to take weeks can now be done in hours“
Next stop was an elegant and beautiful 12th century Benedictine monastery. With no more than 30 minutes between the end of the Vespers – the evening service – and the time when the public would be allowed into the monastery, we carried out a quick reconnaissance and accurately captured the unique domed building, only possible using GeoSLAM’s ’go-anywhere’ device.
Final port of call was a delapidated 19th-century merchant house in the ancient Arab town of Jaffa. The challenge here was to record the building while construction works were in progress, with hoardings and scaffolding obscuring structures. A near impossible task, but the ZEB Revo was still able to collect survey-grade data in a matter of hours, which formed the basis of a working record of elevations, sections and plans.
In under 48 hours Jamie had captured highly accurate 3D images of 3 heritage buildings. Proof indeed that with the ZEB Revo, what used to take weeks can now be done in hours.
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Known control points are captured during a scan and automatically compared and matched to the associated coordinates during the processing stage in Connect. A rigid and/or a non-rigid adjustment can be made to the dataset and an accuracy report is exported, highlighting how successful the transformation was. Users can now view and manipulate the processing parameters to ensure a more accurate match between points.
Align multiple scans using a combination of manual and automatic processes. This workflow can be performed on two or more scans in the same project. Users have a choice to export the aligned scans separately or as a single merged point cloud.
Common data capture scenarios, such as UAV, outdoor, indoor, linear, and vehicle, have been characterised in Connect and data processing pre-sets for each environment have been defined. These can be selected at the beginning of the data processing stage allowing this process to be highly simplified.
Both methods match the scan data from a ZEB Locate system with the GPS data collected from the antenna to georeference the point cloud. When a scan starts and ends in the same place, this is classed as “closed loop”. “Open loop” is when the start and end position of a scan are in different locations. Standard SLAM practices apply to both methods of data collection.
Open Loop SLAM for the ZEB Locate is available on request – let’s talk about it.
Common static points are captured during several scans meaning that these datasets can be automatically aligned. A single point cloud is then exported as if the data was captured in a single scan.
Horizontal and vertical slices can be taken from any location within the point cloud. Horizontal floor slices can also be automatically taken at a given height above the floor as defined in the processing stage.
Mostly used in the construction industry, multiple point clouds can be compared and any areas that have changed are automatically highlighted. Point clouds can also be compared with CAD models – for instance to track progress on a construction site – and PDF reports can be generated to present this information.
Some SLAM software algorithms have been made available as open-source on the internet, but they are purely algorithms and not a product that you can take and use off-the-shelf. SLAM is most successful when it is tightly coupled and designed with specific hardware in mind. A generic SLAM cannot perform as well as one that has been specifically designed for a purpose.
Visual SLAM is closer to the way humans navigate the world, which is why it’s popular with robotic navigation. But in the same vein, vSLAM will have the same image-capture challenges as humans do, for example not being able to look into direct sunlight, or not having enough contrast between the objects picked up in the image. These can be overcome indoors, however, you may need to map a forest, tunnel or urban canyon. While SLAM technologies don’t rely on remote data (meaning you can scan areas where there is no GPS), you do need to ensure the SLAM technology you chose operate well inside, outside, in daylight and darkness.
Mapping a property is time-critical. Ideally, you want to make a single visit and gather sufficient data to create a highly accurate 3D model. Ensure the software you choose transforms 3D point cloud data into actionable information in real-time. This allows you to view and interrogate your data whilst still in the field, and make any adjustments, or collect missed data, then and there.
If you’re trying to map an enclosed environment (e.g. tunnel, mine) or a complex, difficult-to-access space such as a heritage building with tight stairwells and uneven floors, you need to use fully-mobile, adaptable technology. Wheel-based systems, often used with the vSLAM camera, will struggle with access. Handheld devices or LiDAR scanners that can be attached to a drone or pole and still deliver accurate results in a rugged environment are best for navigating hazardous spaces.
While vSLAM is able to provide a qualitative high-level map and sense of the surrounding features, if you’re needing survey-quality accuracy and rich-feature tracking at a local level, you’ll need to consider LiDAR. Cameras require a high-frame-rate and high processing to reconcile data sources and a potential error in visual SLAM is reprojection error, which is the difference between the perceived location of each setpoint
and the actual setpoint.
In order to deliver the depth required for high-quality data, a number of depth-sensing cameras are needed with a strong field of view. In most cases, this isn’t possible, especially as cameras with high processing capabilities typically require larger batteries which weigh down airborne scanners, or limit the time of flight. LiDAR is both faster and more accurate than vSLAM, and can deliver detailed point clouds without expensive (and timely) camera processing.
