SAA is a research and development enterprise; specialising in systems and software for vibration, vision, and sound sensors in IoT and robotics. SAA provision data collectors (DACs) for datamining, pattern recognition, and visualisation of big data sets and streaming data sources. SAA also implement fully integrated end-to-end systems for Industrial Internet-of-Things (IIoT) in collaboration with highly experienced IoT equipment and systems providers.
SAA provisions Machine Learning (ML) and Optimisation modelling, Artificial Intelligence (AI) - trained neural networks, and computer vision (CV) for industrial application.
-BigAnalytics™
S-BigAnalytics™ is a big data, machine learning, and datamining software for IIoT.
It is supported on Linux, MacOS, and MS-Windows computers. S-BigAnalytics™ is also provisioned as a ready-to-use SaaS on Lateral Blast Cloud, which can be accessed on monthly pay-as-you-go basis. S-BigAnalytics™ is a virtual machine based platform that can be installed on any personal computer or in the cloud. It processes raw sensor data such as temperature, vibrations, and accelerations, into:
- Events e.g. a mechanical part's malfunction
- Business Intelligence (BI) about such events e.g. linked events
- New insights into variety of industrial operations
- Detecting anomalies and outliers occurring during plant operation
- Gathering equipment use and staffing statistics
- Predicting critical events
S-BigAnalytics™ SaaS can apply its machine learning models to millions of records, gathering deep BI, in a few seconds.
S-BigAnalytics™ provisions a suite of custom apps for machine learning and datamining on IIoT and camera sensor data.
Mobile phone apps are provided for live monitoring and alerts. All mobile phone apps are also accessible from personal computers; providing device-free access.
ystem Information
SAA provision an essential component for IoT systems*; in the form of a platform that handles real-time data collection, visualisation, and alerts. This platform can be deployed for a range of IoT projects such as but not limited to smart city and smart industry applications - manufacturing equipment, warehouses, civic buildings, public spaces, perimeter security, early warning, hospitals etc.
SAA data collectors (DACs) achieve the highest economy of scale with the entire data collection and visual analytics system being integrated within a single compact platform, making online data analytics and datamining operations possible for dynamic data streams and static data sets simultaneously. In doing so we can provision a very high level of performance at an affordable cost to the end user. The platform scales up with each new DAC, bringing additional storage and processing capacity.
SAA provide a complete in-house solution, with easy to understand documentation, for customers to self-manage their data collection and analytics**.
SAA systems are fully self-contained; no worries about data ownership or to incur on-going and ever increasing cloud rental charges.
If requested, SAA can also provide end-to-end support for the installations. We provide full system analysis and project management services for large projects e.g. multi-site or highly specific deployments, working closely to achieve satisfactory outcomes for all stake holder.
- *Please contact us with the details of your IoTs to check if these can be supported by the DAC.
- **SAA Analytics Levels
- Bir: Charts and Dashboards
- Iki: BI Questions, Datamining
- Uch: Machine Learning, Classification, Regression
ystem Research and Development
Project: High-precision optical system localisation
Objective: Finding precise equipment orientation with IoT motes
Method: Camera enabled reader for fluid level and gyroscopic motion devices embedded in a compact format
Test-bed: Commodity narrow and wide field optical system for field data acquisition coupled with DAC; platform automation with IoT metering and robotic control
Applications:Automatic localisation of surveying systems
Project: Image information retrieval using non-visual analytics
Hypothesis: Some optical sensor data may contain information that is not easily discernible through visual representations.
Objective: Non-visual (informational) artefact discovery from optical sensor data
Method: In-situ data acquisition of naturally graded visual fields with narrow and wide field optical systems; exploration with bio-inspired bigdata analytics
- Noise subtraction
- Associative analyses
- Content-addressable episodic memory
- Contextual data (platform logs, environmental data)
- Data outliers
- CV object-recognition
- Data-object information matrices for ML
Test-bed: Commodity narrow and wide field optical system for field data acquisition coupled with DAC; platform automation with IoT metering and robotic control
Applications: Remote dark object detection, remote site survey, medical diagnostics, autonomous guidance, predictive analysis
* Limited industrial research grants available; EOIs by email below
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