The agricultural industry is looking to technology to solve its challenges such as a labor and food shortage and robots are an important part of that strategy.
Digitizing reality is now possible for workers thanks to technology advances such as the Internet of Things (IoT). This new reality allows workers to benefit from augmented reality (AR), mixed reality (MR) and virtual reality (VR) to solve old problems in new and better ways.
Smart manufacturing and the Industrial Internet of Things (IIoT)-enabled technologies can use real-time data to optimize processes and reduce costs for manufacturers.
Set the stage for a successful transition from manual to IIoT-enhanced, predictive maintenance processes.
MIT researchers have developed a system that lets nonspecialists use machine-learning (ML) models to make predictions for medical research, sales, and more.
Deep embedded vision systems can work without operating systems and feature advanced algorithms for processing raw image streams from integrated image sensors.
Integrated manufacturing operations management (iMOM) is designed to increase and sustain business benefits for users such as improved accuracy and thorough implementation.
Researchers at the University of Maryland have developed a method to combine perception and motor commands using the hyperdimensional computing theory, which could fundamentally alter and improve how robots translate what they sense into what they do through artificial intelligence (AI).
MIT researchers have developed an algorithm that accurately aligns partial trajectories in real-time, allowing motion predictors to accurately anticipate the timing of a person’s motion to make human-robot interaction safer.
Extract, transform, load (ETL) software can help improve data gathering for operations technology (OT) applications, but there are major challenges with data integration that companies need to overcome.