Enterprises today face significant inefficiencies that can be solved using Artificial Intelligence, but in most cases, the company and its management are not even aware of this issue and opportunity.   

 

To move forward and accelerate AI adoption, necessitates dealing with four problematic areas.  

1

Data and its volume and complexity continues to explode, especially unstructured data such as video. 

Tegu captures and harnesses video and image data, with data models, and standardised data process workflows

2

The heavy reliance on People for their expertise and experience is in an environment of increased churn, which increases complexity and cost, especially for staff training.

 

Tegu allows repetitive work, expertise, and experience to be modelled and stored in models.

3

Each company has a highly Complex IT Environment, processes and people, and currently do not have flexible AI options to deal with this.

 

Tegu provides platform for re-use of data and models to drive flexibility and enables rapid adoption of an AI solution.

4

Solving Unique Business Problems usually involves multiple products and experts, which increases cost and complexity.  

 

Tegu allows users to adopt a plug-and-play model and platform with the majority of the programming already in place.

Case Study

Animal Conservation

There is growing attention and concern for wildlife conservation from both the government and the private sectors. To accurately track and measure environmental and wildlife conservation, requires accurate validation and estimation of certain species (such a big cats in the wild). For a recent project, a wildlife conservation organization installed more than 100 infrared cameras for every 200 km^2 in wild, mountainous terrain. These infrared cameras collect terabytes of images and videos every other month. Due to other species of animals triggering the camera, or other technical difficulties of the infrared camera, about 60% of the collected images are invalid data. This means human viewing of the images/video is laborious, and potentially inaccurate. Animal conservationists need to manually delete invalid data and then from what is left, identify wildlife species from blurred images that only shows part of an animal. This job requires years of practice and expertise in natural history.

 

Using Tegu, wildlife conservationists can filter invalid data and identify species at the speed of 10 images/second. With one simple click, the exploding volume of images are structured and graphical reports are generated, creating an accurate assessment. 

Smart Airport

“Smart Airport” has become very topical, with a growing number of surveillance cameras installed in airports. The question is how and who will be utilizing this huge new volume of video footage?  

 

To effectively utilize these huge new volumes of video images and unstructured data, airport management teams need to be able to identify each step of analysing the tarmac conditions, taking off/landing timing and issues, video data correlation, and provide real-time analysis and recommendations.

 

gi’s Tegu solution is capable of processing thousands of video data streams of video data. All collected statistical data from video footage can then be seamlessly integrated into the existing airport management platform, delivering a much “smarter” airport.

Power/Utility Grid

Power/Utility Grid Operators utilize gi’s product (Tegu) to continually adapt their computer vision and AI models to learn to detect broken/defective parts in transmission towers. 

 

Using Tegu, image and video data are automated, categorised accordingly and organised into a maintenance report. Traditionally, it takes an experienced worker up to 3 work-days to categorise 10,000 images, before even starting to putting together the maintenance report. 

 

Now with Tegu, it only takes about 2 hours to filter data, categorise images and generate an analysis and report based on these images.

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