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	<title>Uncategorized Archive | Atlantic Tech &amp; Candy</title>
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	<description>World-class underwater computer vision.</description>
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		<title>Measuring What Matters: Estimating Hull Roughness During Routine Biofouling Inspections</title>
		<link>https://atnc.ai/2026/02/estimating-hull-roughness/</link>
		
		<dc:creator><![CDATA[Christian Wiele]]></dc:creator>
		<pubDate>Tue, 24 Feb 2026 07:38:45 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<guid isPermaLink="false">https://atnc.ai/?p=1263</guid>

					<description><![CDATA[<p>When it comes to ship efficiency, size matters—specifically, the size of barnacles on your hull significantly impacts hull roughness. While most underwater inspections focus on identifying the presence of biofouling, understanding the actual dimensions of these organisms is critical for predicting their impact on fuel consumption and vessel performance.</p>
<p>Atlantic Tech &#038; Candy, in partnership with Blue Atlas Robotics and their ROV Sentinus 2, has developed an approach to measure barnacle dimensions during routine biofouling inspections using stereo camera technology. This capability transforms standard inspection footage into quantitative data that operators can use for maintenance planning and performance monitoring.</p>
<p>Der Beitrag <a href="https://atnc.ai/2026/02/estimating-hull-roughness/">Measuring What Matters: Estimating Hull Roughness During Routine Biofouling Inspections</a> erschien zuerst auf <a href="https://atnc.ai">Atlantic Tech &amp; Candy</a>.</p>
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			<p>When it comes to ship efficiency, size matters—specifically, the size of barnacles on your hull significantly impacts hull roughness. While most underwater inspections focus on identifying the presence of biofouling, understanding the actual dimensions of these organisms is critical for predicting their impact on fuel consumption and vessel performance.</p>
<p>Atlantic Tech &amp; Candy, in partnership with <a href="https://blueatlasrobotics.com/">Blue Atlas Robotics</a> and their <a href="https://blueatlasrobotics.com/underwater-inspections/sentinus-rov">ROV Sentinus 2</a>, has developed an approach to measure barnacle dimensions during routine biofouling inspections using stereo camera technology. This capability transforms standard inspection footage into quantitative data that operators can use for maintenance planning and performance monitoring.</p>

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			<h3>Why Barnacle Size Matters More Than You Think</h3>

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			<p>Not all biofouling has the same impact on drag. Research shows that barnacle height is the dominant factor in determining added resistance—far more than coverage area alone. A hull with 10% coverage of 5mm-tall barnacles can experience similar drag penalties as one with 50% coverage of smaller 1.25mm barnacles. This means that knowing how big your barnacles are, not just where they are, is essential for accurate performance predictions.</p>
<p>Hull roughness is typically characterized by parameters like equivalent sand-grain roughness (k_s), which directly influences drag calculations in performance models. By measuring barnacle dimensions, operators can estimate these roughness values and better understand the fuel penalty they&#8217;re facing.</p>

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			<h3>From Inspection Video to Quantitative Hull Roughness Measurements</h3>

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			<p>The stereo camera system on the Sentinus 2 ROV captures paired images that enable distance measurement to the hull surface. Combined with <a href="https://atnc.ai/hullsight-ultimate/">HullSight Ultimate</a>, Atlantic Tech &amp; Candy&#8217;s solution for biofouling analysis, this creates a complete pipeline from raw video to barnacle size estimates:</p>

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<li><strong>Biofouling Detection</strong>: HullSight Ultimate&#8217;s semantic segmentation model identifies and segments barnacles (and other fouling types) in the inspection footage</li>
<li><strong>Distance Estimation</strong>: Stereo vision calculates the distance to the hull, typically 70-80cm during inspections</li>
<li><strong>Size Calculation</strong>: With known distance and camera parameters, pixel measurements convert to real-world dimensions</li>
<li><strong>Statistical Analysis</strong>: Individual barnacles are measured, including detection of barnacle clusters where multiple organisms have merged</li>
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			<a class="qode-prettyphoto qode-single-image-pretty-photo" data-rel="prettyPhoto[rel-1263-2970744453]" href="https://atnc.ai/wp-content/uploads/2026/02/barncale_size-1024x1024.webp" target="_self"><div class="vc_single_image-wrapper   vc_box_border_grey"><img fetchpriority="high" decoding="async" width="300" height="300" src="https://atnc.ai/wp-content/uploads/2026/02/barncale_size-300x300.webp" class="vc_single_image-img attachment-medium" alt="Estimating hull roughness based on barnacle size estimate: from source image to semantic segmentation to size estimate" title="barncale_size" srcset="https://atnc.ai/wp-content/uploads/2026/02/barncale_size-300x300.webp 300w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-1024x1024.webp 1024w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-150x150.webp 150w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-768x768.webp 768w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-570x570.webp 570w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-500x500.webp 500w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-1000x1000.webp 1000w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size-700x700.webp 700w, https://atnc.ai/wp-content/uploads/2026/02/barncale_size.webp 1080w" sizes="(max-width: 300px) 100vw, 300px" /></div></a><figcaption class="vc_figure-caption">left: original image, center: semantic segmentation, right: size estimate (click to enlarge)</figcaption></figure>
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			<p>For a typical inspection frame at 70cm distance, the system achieves approximately 0.5mm resolution—sufficient to characterize barnacles ranging from a few millimeters to several centimeters in diameter.</p>

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			<h3>Handling Real-World Complexity</h3>

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			<p>Barnacles don&#8217;t always grow as isolated individuals. Dense colonization often results in clusters where boundaries between organisms aren&#8217;t visible. The analysis approach accounts for this by using statistical methods to estimate the number of individual barnacles within merged clusters, providing more accurate population counts and size distributions.</p>
<p>In one analyzed frame, the system detected 180 distinct regions but estimated these represented approximately 462 individual barnacles—revealing that nearly one-third of the detected areas were actually clusters. This level of detail helps distinguish between light fouling with a few large barnacles and heavy colonization with many smaller organisms.</p>

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			<h3>Practical Applications</h3>

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			<p>This measurement capability integrates naturally into existing inspection workflows. The same ROV footage used for visual documentation now also provides:</p>

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<li><strong>Quantitative fouling metrics</strong> for maintenance decision-making</li>
<li><strong>Hull roughness estimate</strong> for performance monitoring</li>
<li><strong>Baseline data</strong> for tracking fouling progression between cleanings</li>
<li><strong>Objective measurements</strong> for evaluating coating performance</li>
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			<p>Rather than relying on subjective assessments like &#8220;light,&#8221; &#8220;moderate,&#8221; or &#8220;heavy&#8221; fouling, operators gain specific measurements: median barnacle diameter, coverage percentage, and estimated roughness values that can feed directly into performance models.</p>

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			<h3>Scalable for Large Vessels</h3>

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			<p>This approach scales naturally to large-scale hull inspections. The combination of HullSight Ultimate&#8217;s automated biofouling analysis and the Sentinus 2&#8217;s efficient inspection capabilities enables comprehensive hull surveys on vessels of all sizes. As demonstrated in our recent <a href="https://atnc.ai/2026/01/streamlining-large-scale-hull-inspections-a-case-study-with-blue-atlas-robotics/">case study with Blue Atlas Robotics</a>, the workflow handles thousands of inspection frames, providing complete hull coverage with consistent measurement quality.</p>

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			<h3>Looking Forward</h3>

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			<p>As the maritime industry focuses increasingly on efficiency and emissions reduction, understanding the true condition of hull surfaces becomes more valuable. The ability to quantify biofouling during routine inspections—without specialized equipment or procedures—makes this data accessible as part of normal operations.</p>
<p>The combination of ROV technology, stereo vision, and automated analysis transforms inspection from documentation into measurement, giving operators the information they need to optimize maintenance timing and predict performance impacts with greater confidence.</p>

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			<a class="qode-prettyphoto qode-single-image-pretty-photo" data-rel="prettyPhoto[rel-1263-2070371466]" href="https://atnc.ai/wp-content/uploads/2026/02/sentinus.webp" target="_self"><div class="vc_single_image-wrapper   vc_box_border_grey"><img decoding="async" width="300" height="300" src="https://atnc.ai/wp-content/uploads/2026/02/sentinus-300x300.webp" class="vc_single_image-img attachment-medium" alt="Sentinus ROV with stereo cameras at the center" title="sentinus" srcset="https://atnc.ai/wp-content/uploads/2026/02/sentinus-300x300.webp 300w, https://atnc.ai/wp-content/uploads/2026/02/sentinus-150x150.webp 150w, https://atnc.ai/wp-content/uploads/2026/02/sentinus-768x768.webp 768w, https://atnc.ai/wp-content/uploads/2026/02/sentinus-570x570.webp 570w, https://atnc.ai/wp-content/uploads/2026/02/sentinus-500x500.webp 500w, https://atnc.ai/wp-content/uploads/2026/02/sentinus-700x700.webp 700w, https://atnc.ai/wp-content/uploads/2026/02/sentinus.webp 1000w" sizes="(max-width: 300px) 100vw, 300px" /></div></a><figcaption class="vc_figure-caption">Sentinus ROV with stereo cameras at the center (click to enlarge)</figcaption></figure>
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			<h3>About the Partnership</h3>

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			<p>This work represents a collaboration between Atlantic Tech &amp; Candy and Blue Atlas Robotics, combining expertise in marine efficiency analysis with advanced ROV capabilities. The Sentinus 2 ROV&#8217;s stereo camera system provides the foundation for these measurements during standard underwater inspections.</p>

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			<h3>Want to learn more about Hull Roughness Estimation? Contact Us!</h3>

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</div><p>Der Beitrag <a href="https://atnc.ai/2026/02/estimating-hull-roughness/">Measuring What Matters: Estimating Hull Roughness During Routine Biofouling Inspections</a> erschien zuerst auf <a href="https://atnc.ai">Atlantic Tech &amp; Candy</a>.</p>
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		<title>Role-Based Access Control: Three Levels of Security</title>
		<link>https://atnc.ai/2026/02/role-based-access-control/</link>
		
		<dc:creator><![CDATA[Christian Wiele]]></dc:creator>
		<pubDate>Tue, 10 Feb 2026 09:33:04 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<guid isPermaLink="false">https://atnc.ai/?p=1221</guid>

					<description><![CDATA[<p>Underwater hull inspection involves multiple parties with different responsibilities and access needs. Shipping companies own vessels and need oversight of their entire fleet. Fleet managers coordinate inspection activities across multiple vessels and organizations. Service providers conduct the actual inspections and need access to specific projects they're working on. Each party requires different levels of access to vessel data, inspection projects, and reporting capabilities.</p>
<p>Der Beitrag <a href="https://atnc.ai/2026/02/role-based-access-control/">Role-Based Access Control: Three Levels of Security</a> erschien zuerst auf <a href="https://atnc.ai">Atlantic Tech &amp; Candy</a>.</p>
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			<p>Underwater hull inspection involves multiple parties with different responsibilities and access needs. Shipping companies own vessels and need oversight of their entire fleet. Fleet managers coordinate inspection activities across multiple vessels and organizations. Service providers conduct the actual inspections and need access to specific projects they&#8217;re working on. Each party requires different levels of access to vessel data, inspection projects, and reporting capabilities.</p>
<p>We&#8217;ve implemented a comprehensive Role-Based Access Control (RBAC) system for <a href="https://atnc.ai/hullsight-ultimate/">HullSight Ultimate</a> that provides granular control over what users can see and do in the application. The system operates on three distinct levels, each serving a specific purpose in the security architecture.</p>
<h3>The Three Permission Levels</h3>

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			<h4>1. Navigation-Level Permissions</h4>
<p>The first level controls which modules and pages users can access. When a user logs in, the system determines which navigation items appear in their menu based on their assigned role. For example, an Inspector might only see Projects, Reporting, Documentation, Help, and Profile, while a Fleet Manager has access to additional modules like Vessels, Organizations, and Monitoring.</p>
<p>This level prevents users from even knowing about features they shouldn&#8217;t access. The frontend dynamically generates navigation menus and routes based on the user&#8217;s permissions, ensuring that unauthorized pages cannot be accessed even by manually typing URLs.</p>

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			<h4>2. Model-Level CRUD Permissions</h4>
<p>The second level determines what actions users can perform on different types of data. CRUD stands for Create, Read, Update, and Delete. A role might allow viewing and editing projects but not creating or deleting them.</p>
<p>Consider three different scenarios: An Inspector can view and change projects but cannot add or delete them, meaning they can update inspection findings but cannot create new projects. A Viewer has read-only access to projects &#8211; they can see all project details but cannot modify anything. A Fleet Manager has full CRUD permissions on projects, allowing them to create, view, edit, and delete projects as needed. The system uses these permissions to show or hide action buttons in the interface &#8211; if you don&#8217;t have delete permission, you won&#8217;t see delete buttons.</p>

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			<h4>3. Object-Level Permissions</h4>
<p>The third level controls access to specific instances of data. Even if a user has permission to view projects in general, object-level permissions determine which specific projects they can see.</p>
<p>The system implements this through a hierarchical access group structure. Access flows down the hierarchy: if you have access to an organization, you automatically get access to all vessels in that organization and all projects for those vessels. This hierarchical approach reduces administrative overhead while maintaining fine-grained control.</p>

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			<h3>Role Examples</h3>
<h5>Tenant Admin</h5>
<ul>
<li>Navigation: All modules</li>
<li>CRUD: Full permissions on all models</li>
<li>Objects: Access to everything in the tenant</li>
</ul>
<h5>Fleet Manager</h5>
<ul>
<li>Navigation: Projects, Reporting, Export, Vessels, Hull Sectioning Schemas, Organizations, Biofouling Scales, Monitoring, Documentation, Help, Profile</li>
<li>CRUD: Full permissions on projects, vessels, organizations, hull sectioning, and biofouling scales</li>
<li>Objects: Can be restricted to specific organizations/vessels or granted unrestricted access</li>
</ul>
<h5>Inspector</h5>
<ul>
<li>Navigation: Projects, Reporting, Documentation, Help, Profile</li>
<li>CRUD: Can view and change projects</li>
<li>Objects: Access limited to assigned projects only</li>
</ul>
<h5>Viewer</h5>
<ul>
<li>Navigation: Projects, Reporting, Documentation, Help, Profile</li>
<li>CRUD: View-only access</li>
<li>Objects: Access limited to assigned projects only</li>
</ul>

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			<h3>Unrestricted Access Option</h3>
<p>Roles can be configured with an &#8220;unrestricted access&#8221; flag. When enabled, users with that role bypass object-level filtering while still respecting CRUD permissions. This is useful for organizations that want certain roles to see all data without the complexity of access group assignments. For example, a Fleet Manager role with unrestricted access can view all projects in the tenant, but if they don&#8217;t have delete permission, they still cannot delete any projects. This separates the &#8220;what can you do&#8221; question (CRUD permissions) from the &#8220;what can you see&#8221; question (object-level access).</p>

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			<h3>Access Groups and Hierarchical Filtering</h3>
<p>Access groups simplify permission management by grouping organizations, vessels, and projects together. Instead of assigning individual users to individual projects, administrators assign users to access groups, and those groups contain the relevant entities.</p>
<p>The hierarchical nature means you can grant access at any level:</p>
<ul>
<li>Grant access to an organization → user sees all vessels and projects in that organization</li>
<li>Grant access to a vessel → user sees all projects for that vessel</li>
<li>Grant access to specific projects → user sees only those projects</li>
</ul>
<p>&nbsp;</p>
<p>Users can belong to multiple access groups, and their permissions are combined. If one access group grants access to Organization A and another grants access to Project X (which isn&#8217;t in Organization A), the user gets access to both.</p>

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			<h3>Entity Groups for Bulk Management</h3>
<p>Organization Groups, Vessel Groups, and Project Groups allow administrators to bundle entities together for easier permission assignment. Instead of individually selecting 50 vessels, you can create a &#8220;Container Fleet&#8221; vessel group and assign it to an access group in one action.</p>

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			<h3>Audit Trail</h3>
<p>Every permission change is logged in a comprehensive audit trail. The system tracks who made what changes, when they were made, and from which IP address. This includes:</p>
<ul>
<li>Role assignments and removals</li>
<li>Access group membership changes</li>
<li>Permission modifications (navigation items, CRUD permissions)</li>
<li>Entity access grants and revocations</li>
<li>Role and access group creation, updates, and deletions</li>
</ul>
<p>Each audit log entry captures the user who performed the action, the affected user or entity, and detailed information about what changed. For role assignments, the system records both the old and new roles. For entity access changes, it logs the entity type, entity IDs, and whether access was granted or revoked.</p>
<p>The audit interface displays these logs in a filterable table with color-coded action chips: green for additions and grants, red for deletions and revocations, orange for updates, and blue for copy operations. Only tenant administrators can access the audit logs, ensuring that the security trail itself remains secure.</p>
<p>The audit logging is designed to never interfere with operations. If logging fails for any reason, the main operation continues successfully. This ensures that audit functionality doesn&#8217;t become a point of failure for critical permission changes.</p>

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			<h3>Benefits of This Approach</h3>
<p><strong>Separation of Concerns:</strong> The three-level system cleanly separates module access, action permissions, and data visibility. This makes it easier to reason about what a user can and cannot do.</p>
<p><strong>Flexibility:</strong> Organizations can choose between unrestricted roles (simpler, broader access) and restricted roles with access groups (more complex, tighter control) based on their security requirements.</p>
<p><strong>Hierarchical Efficiency:</strong> Granting access at the organization level automatically cascades to vessels and projects, reducing administrative work while maintaining security.</p>
<p><strong>Role-Based Management:</strong> Permissions are tied to roles, not individual users. When you need to change what Inspectors can do, you update the Inspector role once rather than updating dozens of user accounts.</p>
<p><strong>Scalable:</strong> The system uses efficient database queries with set operations and proper indexing, ensuring performance even with large numbers of users and entities.</p>
<p><strong>Gradual Adoption:</strong> Organizations can start with unrestricted roles and add object-level restrictions later as their needs evolve. The system doesn&#8217;t force complexity on those who don&#8217;t need it.</p>
<p>The RBAC system provides the foundation for secure multi-user collaboration while maintaining the flexibility to adapt to different organizational structures and security requirements.</p>

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			<h3>Want to learn more about HullSight Ultimate? Contact Us!</h3>

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			<div class="vc_single_image-wrapper   vc_box_border_grey"><img loading="lazy" decoding="async" width="1000" height="552" src="https://atnc.ai/wp-content/uploads/2026/01/atnc_ui.webp" class="vc_single_image-img attachment-large" alt="HullSight Ultimate UI" title="atnc_ui" srcset="https://atnc.ai/wp-content/uploads/2026/01/atnc_ui.webp 1000w, https://atnc.ai/wp-content/uploads/2026/01/atnc_ui-300x166.webp 300w, https://atnc.ai/wp-content/uploads/2026/01/atnc_ui-768x424.webp 768w, https://atnc.ai/wp-content/uploads/2026/01/atnc_ui-700x386.webp 700w" sizes="auto, (max-width: 1000px) 100vw, 1000px" /></div>
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</div><p>Der Beitrag <a href="https://atnc.ai/2026/02/role-based-access-control/">Role-Based Access Control: Three Levels of Security</a> erschien zuerst auf <a href="https://atnc.ai">Atlantic Tech &amp; Candy</a>.</p>
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		<title>Streamlining Large-Scale Hull Inspections: A Case Study with Blue Atlas Robotics</title>
		<link>https://atnc.ai/2026/01/streamlining-large-scale-hull-inspections-a-case-study-with-blue-atlas-robotics/</link>
		
		<dc:creator><![CDATA[Christian Wiele]]></dc:creator>
		<pubDate>Tue, 27 Jan 2026 16:57:30 +0000</pubDate>
				<category><![CDATA[Uncategorized]]></category>
		<guid isPermaLink="false">https://atnc.ai/?p=1191</guid>

					<description><![CDATA[<p>In December 2025, we successfully demonstrated the power of combining advanced robotics with AI-driven analysis during a large-scale hull inspection in Aarhus, Denmark. In partnership with <a href="https://www.blueatlasrobotics.com">Blue Atlas Robotics</a> (BAR), we inspected a 200m container vessel, proving that comprehensive biofouling assessments can be both rapid and highly detailed.</p>
<p>Der Beitrag <a href="https://atnc.ai/2026/01/streamlining-large-scale-hull-inspections-a-case-study-with-blue-atlas-robotics/">Streamlining Large-Scale Hull Inspections: A Case Study with Blue Atlas Robotics</a> erschien zuerst auf <a href="https://atnc.ai">Atlantic Tech &amp; Candy</a>.</p>
]]></description>
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			<p>In December 2025, we successfully demonstrated the power of combining advanced robotics with AI-driven analysis during a large-scale hull inspection in Aarhus, Denmark. In partnership with <a href="https://www.blueatlasrobotics.com">Blue Atlas Robotics</a> (BAR), we inspected a 200m container vessel, proving that comprehensive biofouling assessments can be both rapid and highly detailed.</p>

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			<h3>The Inspection: Precision at Speed</h3>
<p>The physical inspection was carried out by BAR using their Sentinus ROV. Known for its efficiency, the Sentinus covered almost the entire port and starboard sides of the vessel—scanning 49 distinct hull sections and niche areas—in just about <strong>4 hours</strong>.</p>
<p><img loading="lazy" decoding="async" class="size-medium wp-image-1184 alignright" src="https://atnc.ai/wp-content/uploads/2026/01/sentinus_ops-300x225.webp" alt="Blue Atlas Robotics ROV Operator" width="300" height="225" srcset="https://atnc.ai/wp-content/uploads/2026/01/sentinus_ops-300x225.webp 300w, https://atnc.ai/wp-content/uploads/2026/01/sentinus_ops-768x576.webp 768w, https://atnc.ai/wp-content/uploads/2026/01/sentinus_ops-800x600.webp 800w, https://atnc.ai/wp-content/uploads/2026/01/sentinus_ops-700x525.webp 700w, https://atnc.ai/wp-content/uploads/2026/01/sentinus_ops.webp 1000w" sizes="auto, (max-width: 300px) 100vw, 300px" /></p>
<h3>The Analysis: Powered by HullSight Ultimate</h3>
<p>With the physical scan complete, the focus shifted to data analysis using <strong>HullSight Ultimate</strong>. We processed <strong>5.5 GB of video material</strong>, consisting of individual video files for each of the 49 sections.</p>
<p>The speed of the workflow was unprecedented. From the start of the video upload to the delivery of the final report, the entire process took approximately <strong>1 hour</strong>.</p>
<p>During this short window, HullSight Ultimate:</p>
<ul>
<li>Automatically processed the video footage.</li>
<li>Extracted roughly <strong>850 representative images</strong>.</li>
<li>Analyzed every image using our advanced <strong>biofouling AI model</strong>.</li>
<li>Compiled the results into a comprehensive <strong>54-page PDF report</strong>.</li>
</ul>

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			<h3>Actionable Results</h3>

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			<p>The generated report delivered immediate, actionable insights into the vessel&#8217;s condition through a comprehensive overview of all inspected hull sections with their corresponding biofouling ratings. HullSight Ultimate&#8217;s flexible biofouling scales can be fully customized by customers to align with specific reporting requirements and industry standards, ensuring the analysis meets both internal quality protocols and external regulatory expectations.</p>
<p>This tailored approach provides vessel operators with precise, relevant data that supports informed maintenance decisions and compliance reporting.</p>

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			<p>The report provides comprehensive high-level statistics for each vessel side, delivering detailed overviews that include precise biofouling percentages, total count of analyzed images, and calculated overall biofouling ratings based on the selected assessment scale.</p>
<p>This side-by-side analysis enables quick comparative assessment between port and starboard surfaces, helping vessel operators identify patterns, prioritize maintenance areas, and track fouling distribution across the entire hull.</p>

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			<p>Each inspected hull section received comprehensive documentation with detailed statistical analysis—including fouling percentages, median values, minimum/maximum ranges, total analyzed images, and overall biofouling ratings—paired with carefully selected sample images that provide vessel operators with a clear, verifiable picture of the hull&#8217;s condition.</p>
<p>The three representative images strategically showcase areas of maximum, average, and minimum fouling, delivering immediate visual insight into fouling distribution patterns and helping operators quickly determine whether marine growth is uniformly distributed or concentrated in specific zones requiring targeted attention.</p>

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			<h3>Conclusion</h3>
<p>This operation in Aarhus highlights the synergy between Blue Atlas Robotics&#8217; hardware and HullSight Ultimate&#8217;s software. Together, we delivered a complete, high-fidelity inspection of a 200m vessel with minimal downtime, turning gigabytes of raw video into a finalized, actionable report in record time.</p>

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			<h3>Interested in a Large Scale Hull Inspection? Contact Us!</h3>

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			<div class="vc_single_image-wrapper   vc_box_border_grey"><img loading="lazy" decoding="async" width="800" height="600" src="https://atnc.ai/wp-content/uploads/2026/01/inspection.webp" class="vc_single_image-img attachment-large" alt="Hull inspection with HullSight Ultimate" title="inspection" srcset="https://atnc.ai/wp-content/uploads/2026/01/inspection.webp 800w, https://atnc.ai/wp-content/uploads/2026/01/inspection-300x225.webp 300w, https://atnc.ai/wp-content/uploads/2026/01/inspection-768x576.webp 768w, https://atnc.ai/wp-content/uploads/2026/01/inspection-700x525.webp 700w" sizes="auto, (max-width: 800px) 100vw, 800px" /></div>
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</div><p>Der Beitrag <a href="https://atnc.ai/2026/01/streamlining-large-scale-hull-inspections-a-case-study-with-blue-atlas-robotics/">Streamlining Large-Scale Hull Inspections: A Case Study with Blue Atlas Robotics</a> erschien zuerst auf <a href="https://atnc.ai">Atlantic Tech &amp; Candy</a>.</p>
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