Mindtrace's
Brain-Sense™ Technology
The future of Artificial Intelligence, Machine Learning and solution integration.
TECHNOLOGY
What is the Brain-Sense™ Platform?
The Brain-Sense™ platform contains different AI Brains, technologies and learning techniques to prepare and process client data, creating custom AI Brains and solutions for our clients. The platform’s architecture is split into two different verticals, Asset Inspection and Precision Defect Detection. Below showcases the Brain-Sense™ Platform’s architecture and the associated AI brains.
Brain-Sense™ Platform Architecture
Verticals
Asset Inspection
Mindtrace offers a comprehensive end-to-end solution for Point Cloud Data Processing, transforming LiDAR data within weeks, not months. Creating a proactive approach to Asset Inspection and Vegetation Management. To offer this solution, Mindtrace processes the data through 3 different AI Brains, the C-Brain, V-Brain and A-Brain.
01
Asset Inspection
Classification Brain (C-Brain)
Mindtrace’s C-Brain classifies Point Cloud data within weeks, compared to traditional classification that takes months.
The Cbrain can classify the following:
- Vegetation Management - Ground Low/Medium/High Vegetation Building Tower/Pole Wire
- Extended Classification - Water Railroad Roads (unpaved, highway, street) Wire by Voltage Wire by type (shield/phase/guy/communication wire) Thinned Ground/Veg
- The C-Brain is capable of classifying over 45 classes, including custom client requests
02
Asset Inspection
Vectorisation Brain (V-Brain)
Once the C-brain has Classified the Point Cloud, it is transferred into the Mindtrace Vbrain for Vectorisation, producing 2D & 3D Vectors of powerline assets within hours.
- 2D & 3D Vectors generated
- Dangerous vegetation highlighted
03
Asset Inspection
Analytics Brain (A-Brain)
After Point Cloud Classification, Mindtrace’s A-Brain provides the following standard analytics reports to give the customer insight into the current and future risks associated with their network:
- Your entire network and its exact coordinates.
- Current and upcoming intrusions and their severity. Providing actionable information on the exact location, type of intrusion and severity.
- Pole Lean Assessment so you can be proactive in fixing poles before they’re down.
Results
Verticals
Precision Defect Detection
Mindtrace’s Precision Defect Detection solution integrates seamlessly into a client’s organisation, rapidly enhancing their defect detection capabilities. Below we walk you through the standard process undertaken with our clients to create a custom AI solution and brains, from data collection to solution integration.
1.
Data collection and input
Mindtrace collaborates with clients to support their data collection process. Minimal unlabelled data is required due to the Mindtrace Brain-Sense™ Framework augmenting unlabelled data, creating a sufficient data set to train and create an AI Brain that delivers state-of-the-art performance.
Consequently reducing barriers to entry for organisations beginning their AI journey whilst simultaneously creating significant savings on labelling time and associated costs.
2.
Engaging the Brain-Sense™
AI Framework
The existing data is analysed utilising the Brain-Sense™ Framework to understand the learning techniques that can be utilised to create a bespoke AI brain that meets the customer’s requirements.
Unsupervised learning
Machine learning algorithms that analyse unlabelled data without human intervention.
Self-supervised learning
A form of unsupervised learning that self-generates labels to learn visual representations of the data.
Semi-supervised learning
Combining labelled and unlabelled data to effectively perform machine learning tasks.
Few-shot learning
A Machine learning algorithm that requires minimal training samples to be effective.
Knowledge Transfer
Harnessing existing AI brains to enhance the training of new models.
3.
Bespoke Brain Creation
The bespoke AI brain(s) are created that successfully meet the client’s use case. Mindtrace holds an existing library of AI Brains that can be adapted and utilised, resulting in significant reductions in rollout time. Below are the standard types of brains that are deployed with Precision Defect Detection.
01
Precision Defect Detection
Classification Brain for Defects (C-Brain)
Mindtrace supports over 1000 classes and defect types. The quality defect standards are based on the customer’s requirements.
- Product Quality Grading - Good/Bad/Faulty.
- Defect Classifications - Scratch / Oxidation / Corrosion /Nick / Missing parts.
- Manufacturing Product Identification - Brands/Logos/Serial Numbers.
02
Precision Defect Detection
Defect Detection Brain (D-Brain)
Mindtrace’s Defect Detection Brain identifies the exact location of the defect within the image. The brain supports most imaging formats, including RGB, X-RAY and DCOM to localise defective regions.
- Highlighting defective regions with confidence levels.
- Bounding box around defected regions, or heatmap visualisations to pinpoint defective regions.
03
Precision Defect Detection
Anomaly Detection Brain (A-Brain)
Mindtrace supports a variety of industrial environments to detect anomaly behaviours:
- Distinguish product qualities into anomalies and normal.
- Identify and isolate anomalies visually through bounding box segmentation or a heatmap.
4.
Solution integration
Once created, the brain is deployed with the client’s organisation, using dedicated hosts, SoC or Cloud Technologies. We commonly deploy on android tablets, windows computers and companies’ internal devices.
Whilst deployed, the brain is continuously learning on the production line and from knowledge sharing with other brains and devices.
