In today's society, where independent living is becoming increasingly important, it can be extremely constricting for those who are blind. Blind and visually impaired (BVI) people face challenges because they need manual support to prompt information about their environment. In this work, we took our first step towards developing an affordable and high-performing eye wearable assistive device, DRISHTI, to provide visual navigation assistance for BVI people. This system comprises a camera module, ESP32 processor, Bluetooth module, smartphone and speakers. Using artificial intelligence, this system is proposed to detect and understand the nature of the users' path and obstacles ahead of the user in that path and then inform BVI users about it via audio output to enable them to acquire directions by themselves on their journey. This first step discussed in this paper involves establishing a proof-of-concept of achieving the right balance of affordability and performance by testing an initial software integration of a currency detection algorithm on a low-cost embedded arrangement. This work will lay the foundation for our upcoming works toward achieving the goal of assisting the maximum of BVI people around the globe in moving independently.

The digital transformation in manufacturing is accelerating. This means that companies that make things must move faster to innovate their products and transform the way those products are delivered from design to procurement to manufacturing to sustainment. They don't have to go at it alone. A 2020 Deloitte and MAPI Study finds ecosystems can create a competitive edge for manufacturers facing ongoing disruption.1 Today, we'll dive into a component of this ecosystem, Computer Vision. Computer Vision is one of the many Artificial Intelligence solutions that will continue to transform manufacturing.

This story is part of a collection of pieces on how we work today, from video conferencing to using productivity apps for off-label purposes to Silicon Valley culture. When Tony Huffman stepped away from the production line at the Denso auto part factory in Battle Creek, Michigan, to talk with WIRED earlier this month, the workers he supervised were still being watched--but not by a human. A camera over each station captured workers' movements as they assembled parts for auto heat-management systems. The video was piped into machine-learning software made by a startup called Drishti, which watched workers' movements and calculated how long each person took to complete their work. "In the past, we would take a line that was struggling and bring a bunch of people down with stopwatches to try and make it better," Huffman says--at least for problems that seemed serious enough to justify the time and expense.

When Tony Huffman stepped away from the production line at the Denso auto part factory in Battle Creek, Michigan, to talk with WIRED earlier this month, the workers he supervised were still being watched--but not by a human. A camera over each station captured workers' movements as they assembled parts for auto heat-management systems. The video was piped into machine-learning software made by a startup called Drishti, which watched workers' movements and calculated how long each person took to complete their work. "In the past, we would take a line that was struggling and bring a bunch of people down with stopwatches to try and make it better," Huffman says--at least for problems that seemed serious enough to justify the time and expense. Drishti tirelessly logs the "cycle time" for every worker and station all day, for every shift.

Employees toil at lines, doing the same task, repeatedly, in order to assemble a final product. A line stoppage or bottleneck can cost a fortune. What if the manufacturer could see what was going on, in real time, and fix any issues before they become real problems? Or come up with ways to make the process run smoother and more efficiently? That's the basic idea behind Drishti Technologies, a four-year-old startup cofounded by Prasad Akella, a 57-year-old Indian entrepreneur who's best known for leading the General Motors team that developed collaborative robots in the 1990s.

With 340,000 trained volunteers in 189 countries and 140 languages, 7 Cups has an unparalleled reach in the behavioral health space.

In late May, Chinese facial recognition technology developer SenseTime Group announced it had raised $620 million in a second round of funding. The raise valued the company over $4.5 billion, making it the world's most valuable AI unicorn. SenseTime reportedly became profitable last year. Meanwhile, UiPath--an enterprise robotic process automation (RPA) software company--brought in $153 million in a massive Series B round led by previous investor Accel. UiPath said the round pushed it into unicorn status and followed a record year of growth.

NEW DELHI: Accenture today said it has developed an artificial intelligence powered solution to help visually impaired people improve the way they experience the world around them and enhance their productivity in the workplace. The solution, called Drishti, was developed as a part of Accenture's focus on Tech4Good, which aims to apply technology to improve the way the world lives and works by solving complex social challenges, a company release said. Accenture, plans to introduce Drishti to more than 100 visually impaired employees in India. The solution is currently being piloted at Accenture in South Africa, and a Spanish language version is being tested with Accenture employees in Argentina. Drishti, which means'vision' in Sanskrit, provides smart phone-based assistance using AI technologies such as image recognition, natural language processing and natural language generation capabilities to describe the environment of a visually impaired person.