Sensor Analytics Australia 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.

-BigIoT™

S-BigIoT™ is an open source Raspbian image for RPI3 and above. S-BigIoT collects inputs from a variety of directly attached sensors, temperature, vibration, moisture etc supported IoT motes, ThingWave,NCD and USB devices. mics, cameras, Arduino boards It securely and reliably uploads device data to an S-BigAnalytics instance running anywhere on the Internet. Just-in-time (time_t=now) reports can be obtained on key operational statistics and business intelligence. Equipment monitoring, production area statistics, historical analyses, OHS related data logging, data forensics, supply-chain forecasting, predictive maintenance, perimeter security, public area statistics, computer-vision, heat-maps, alarms, quarantine, biosecurity, negative-pressure monitoring, chemical-biological-radiological (CBR) dispersion, environmental monitoring, flood-mapping enhancement are some of the functions that can be provisioned by this system. Realtime sensor readings are also available through a live web-based dashboard. S-BigAnalytics and S-BigIoT together form a unified end-to-end IoT data acquisition & processing framework for industrial, workplace, public health, security, and environmental applications.

-BigAnalytics™

S-BigAnalytics UIs

S-BigAnalytics™ is an open source 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

R&D: Computer-Vision Analytics

Remote Object Recognition

Object recognition at very high-magnification with transient atmospheric compensation.

Application: Hairline crack detection in wind turbines and other relatively inaccessible installations.

Status; available.

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

Contact

Sensor Analytics Australia
PO Box 388
Mount Waverley Vic 3149
ABN 97 716 556 047
Phone: +61 DXJ GE GINC