Development for Drone OS
Microfrontend,Vue,React,Bootstrap,Konva,Mapbox GL,Pusher,SCSSSummary
End-to-end comprehensive drone-based project management solution integrating map navigation, smart clustering, AI defect detection, customizable dashboards, image galleries, and precision editing tools. Streamlined workflows with role-based access, support ticketing, and custom report generation.
Project Management
The Globe view is the foundation for all project management. This interactive tool enables tasks like project creation, updates, and deletions, all connected to the map. Users can easily access this global perspective to navigate project sites, gather data summaries, identify clustering trends, and smoothly perform project management actions. This showcases the platform's commitment to user-friendly and efficient project management.
Personalized Dashboard
The Dashboard consolidates essential information like overall statistics, project growth, activities log, and subscriber trends. Users have the freedom to personalize their dashboard by adding, removing, or rearranging widgets, which are not only draggable but also adjustable in layout. This customization extends to fitting widgets to their layout preferences. Additionally, users can seamlessly integrate dataset data of their choice into widgets, enhancing the dashboard's usefulness
Upload to Cloud & AI Defect Detection
This system streamlines the process of transferring drone-captured images to the cloud effortlessly. Uploading is a breeze—just drag and drop images anywhere on the page. Once the upload is complete, the system automatically extracts EXIF Data in the background, followed by smart clustering. Based on this data, the system suggests existing missions and projects for the user to select or merge with existing clusters. As this unfolds, thumbnails are generated, and simultaneous defect detection occurs on the images, with real-time display of results using web sockets
Visual and Thermal Images Gallery
The Visual and Thermal Images Gallery consolidates cloud-uploaded images into a user-friendly gallery, organized by cluster. This gallery presents two distinct image modes: visual images and thermal images. Thermal images, taken via a drone thermal camera, are subsequently uploaded to the system. The system handles automatic EXIF data extraction and executes smart clustering, categorizing them as visual or thermal. This automation eliminates the need for manual image splitting, especially considering the drone's frequent flights, each with varying modes (visual or thermal), occurring throughout the day.
Smart Clustering
Smart Clustering is powered by artificial intelligence methods such as K-means and Centroid techniques. Upon completion of all cloud uploads, the system's algorithm assumes control, automatically organizing the raw data. It achieves this by discerning specific details from the images, encompassing focal length, sensor dimensions, image proportions, GPS coordinates, angles and altitudes associated with flight, and even the orientation of the gimbal. The outcome of this process is the creation of well-arranged clusters. In cases where clusters show a tendency to overlap, the system can facilitate their merging, particularly if they are situated in the same geographical vicinity
Visual and Thermal Photo Editor
The Project Editor is divided into two main types: Visual Photo Editor and Thermal Photo Editor. In the Visual Photo Editor, users can annotate, review, and validate images. Annotations come in two forms: automatic detection via background AI or manual user drawing. AI-detected defects have preset categories for user approval or rejection, while manual annotations let users choose defect categories. In the Thermal Photo Editor, the focus is on identifying hotspots and calculating Delta Temperature. Users can also adjust image color palettes for better clarity of objectives.
Label Management
Label Management customizes data set labels to enable smart filtering on the user dashboard and effectively organizes label collections. Users can manually organize asset layers and labels within collections, while labeling equipment aids in verifying asset locations, especially when clusters don't accurately represent asset positions. This feature also streamlines asset management by simplifying searches and filters for assets and their components. Beyond AI defect annotations, users can manually identify defects in images or videos using the project editor. If the AI algorithm misses anything, users can add their own labels.
User Role and Permission
In User Management, roles like super admin, admin, project manager, pilot, data analyst, and client define specific permissions. Each role comes with its own responsibilities. Roles within user management can view and create other roles. System roles include a role name, user count, and description. Permissions in this feature enable users to view content and edit assigned projects, while admins can configure settings and permissions. Resource-based permissions involve access to a project list for viewing or editing. Was this response better or worse? Better Worse Same
Support Ticketing
The Support Ticketing System is a key feature with two main functions: Feature Requests and Bugs Reports. It tracks and manages issues, letting users record and follow their progress until resolution. The Bugs Report function ensures smooth operations and user-friendly service, allowing direct issue submission for operational bugs
Custom Report Generation
Custom Report Generation enables users to create reports specific to their chosen projects, missions, towers, or defect annotations. The reporting template follows a standard format accessible to all users. Users can preview and customize the report content before generating it. This feature provides various functions for report creation, including content filtering, text editing, report preview, and the option to download the final report