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Leveraging data at a massive scale with edge devices and edge servers - for purposes like asset tracking, predictive maintenance, fault inspection etc.  and the emergence of IoT, Machine Vision Systems, Robots, Autonomous Vehicles etc. 
Computer Robot

Machine Vision and improvement in product quality 

Manual inspection on the factory floor, once a priceless expertise is today looked differently with the large swathe of wasted resources, rejection of finished goods due to every real or imagined defect which add to the cost of production and decreasing bottom lines in a competitive market. 


But, with evolving Factory Automation and IoT solutions, good parts being mistakenly labeled flawed or defective components going unnoticed and labeled good, have been largely reduced.  

Computer Vision (CV) based systems are able to overcome the need for manual inspection based on human accuracy to identifying every fuzzy ridge, black mark, blur, rough, uneven etc. kind of manufacturing defect thereby classifying products for refinishing or rejection based on the quality and inspection standards.  These systems get further fine tuned and improve the efficiencies further with the incorporation of Machine Learning and Deep learning methodologies, where, the software systems learn from historic labeled image and datasets, solving problems and increasing not just accuracy but increasing efficiency, cutting costs and improving quality.

Modern Beer Brewery
Predictive Maintenance

Predictive maintenance is the strategy of diagnosing potential equipment malfunctions in real time in order to prevent failures. The failure of machines or equipment is expensive in terms of repair costs, lost productivity, and missed customer delivery times and expectations.

Technicians have typically conducted routine diagnosis, inspections, and preventive maintenance according to fixed schedules, which is a costly and labor-intensive process. The transition from reactive maintenance to predictive maintenance allows the opportunity to intervene before downtime occurs. 

Predictive maintenance is widely considered to be the obvious next step for any business with high-capital assets, harnessing machine learning to control rising equipment maintenance costs. Predictive maintenance takes data from multiple and varied sources, combines it, and uses machine learning techniques to anticipate equipment failure before it happens.

Read how Essilor uses Dataiku for Predictive Maintenance

Vaccine Production Line

AI on a new wavelength - Autonomous virus-killing robots fight Covid-19

A certain range of ultraviolet light known as UV-C has been clinically proven to kill complex viruses and bacteria and has been used in hospitals for disinfection processes for the last decade.


Though there hasn’t been any conclusive research on the effects of UV-C on the SARS-CoV-2 virus that can cause the COVID-19 illness yet, studies have shown that it can be used against other coronaviruses such as SARS-CoV-1.1 The UV-C radiation warps the structure of a virus’s or bacteria’s genetic material and prevents the viral particles from reproducing. Early findings from studying UV-C’s effectiveness against SARS-CoV-2 at Columbia University’s Center for Disease and Immunity have been promising.

UV-C robots have been used to sterilize hospitals, but most aren’t designed to work with humans in the room. They blast light that can be dangerous to humans in large doses, requiring rooms to be vacated for the safety of healthcare workers or patients


Read how a startup in Ireland called Akara, has developed a product called Violet, a prototype designed to use motion sensors, an Intel® Movidius™ Vision Processing Unit etc. that allows the slim and nimble Violet to work around the people in the room, navigate to shadowy corners, clean surfaces and automatically switch off before anyone enters her limited field of ultraviolet rays.

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