Machine Learning

Artificial intelligence at its finest

Big data is a double edged sword.

It has allowed scientists, businesses and society as a whole to understand the world like never before, to develop strategy and execute plans with ever increasing effectiveness. But the availability of Big Data raises the bar for operating efficiency in any organisation. Businesses who don't jump onto the band wagon get left behind and miss out on the growth brought forth by the latest technological revolution.

Fortunately, the proverbial band wagon just got upgraded with equally revolutionary advances in the field of Machine Learning. Scientists and engineers have developed software systems that can now learn about the functions of the world through Big Data, and they do so with ever improving speed and accuracy.

Machine Learning and Data Analytics are important aspects of what we do at Kinetic Vision. We develop intelligent software systems that can make sense of the large volumes of data your organisation might have, and then perform tasks such as forecasting events, identifying trends, recognising patterns, and predicting behaviour. These systems can be deployed anywhere a computer can be, even on the cloud and utilised with mobile devices.


Use Cases

Scenario

A large corporation has a requirement to regularly inspect and maintain its physical infrastructure that is distributed all over the country. While they have a system in place to capture images of their assets, the amount of data being collected is too large for any individual or team to analyse and categorise manually. They require a solution that is both fast and cost effective.

Solution

A convolutional neural network is trained to inspect images of their assets and to detect and report any defects found. Images are automatically fed into the neural network via the internet. After inspection, reports are automatically generated and issues highlighted to the human supervisor. If necessary, the neural network can be duplicated with ease to increase inspection throughput.

Scenario

A hospital network wants to implement a medical surveillance system that can highlight human errors as they arise, and even warn doctors of any impending outbreak. The disease of interest is a certain fungal infection in the lungs detected via CT scans of the chest cavity. Radiologists who are experts in CT scans are rare and expensive to hire.

Solution

A neural network is trained using anonymous CT scans of both healthy and infected patients. This allows the network to automatically identify fungal infections right at the point of scanning and even before doctors have had a chance to review the data. Any anomalies are highlighted to the doctor. At the same time, scan information from multiple hospitals are automatically aggregated and analysed as a whole. This improves the chances of detecting an outbreak and containing it from the general population.


Scenario

A local retail chain store wants to better understand their customer base and to improve the overall shopping experience, both in-store and online.

Solution

Sales data is analysed using various methods of data analytics. This can be performed in real time by a computer as sale transactions are registered in their various stores around the country and online. Management has the ability to log online and view live reports on how the business is performing. Additionally, a recommendation system is introduced to the online store. Online shoppers are now guided through a personally tailored shopping experience in which predictive analytics is used to identify selling points relevant to each shopper.

Scenario

YOUR organisation has a problem to solve.

Solution

If you have the data, we have the solution. A study of the problem will be made by us. We will then propose a detailed solution along with an action plan. There is no obligation to take on our services in any way.

Get in touch for an interesting discussion.


Some Machine Learning platforms we work with

Interested to know more?