Fieldwork Robotics Ltd. (“Fieldwork”), developers of selective, adaptive and modular harvesting robots, is pleased to announce that it has developed a new robotic model: the human pickers. The company is also working with Costa Group, Australia’s leading producer of fresh fruit and vegetables. The agreement will see Fieldwork’s robots deployed for trials at Costa berry farms over the next 12 months, with field trials taking place from Q1 2025.
Researchers explored the innovative "Immutably" platform by Context Labs, designed to combat greenwashing by providing transparent, verifiable emissions data using advanced analytics and blockchain technology. The platform, developed by Dan Harple SM '13, helps organizations accurately measure, monitor, and verify their environmental impact, driving genuine sustainability efforts across various industries.
A team of researchers from Osaka Metropolitan University have recently evaluated the environmental costs of artificial intelligence (AI), revealing the requirement for global sustainability initiatives.
Recently, scientists at the US Department of Energy’s (DOE) Argonne National Laboratory, in close collaboration with researchers Aditya Grover and Tung Nguyen at the University of California, Los Angeles, began developing large artificial intelligence (AI) models for weather forecasting, known as foundation models.
Bin Hu and colleagues published a study in ACS Analytical Chemistry on establishing mobile detection systems for hazardous gases and volatile organic compounds (VOCs) by designing remote-controlled sampling devices such as aerial drones and miniature remotely operated ships.
Researchers, in a study published in The Innovation, developed a bionic spine for soft robots inspired by vertebrate animals' spines. By integrating sensing and actuation into a single device using materials like lead zirconate titanate (PZT), the bionic spine enables complex motions and behaviors without external sensors.
Researchers explore the transformative impact of automation and robotics on environmental sensing. They explored cutting-edge technologies such as environmental sensor networks (ESNs), unmanned aerial systems (UASs), robotics, and deep learning (DL), discussing their applications, challenges, and potential.
In a recent paper published in the Proceedings of the AAAI Conference on Artificial Intelligence, an interdisciplinary team from Washington State University has developed a new computer model, utilizing advanced artificial intelligence.
In a world where electrification is sourced more and more from variable sources, such as solar and wind power, researchers have reported the development of artificial intelligence algorithms designed to respond quickly when the network’s voltage balance is threatened.
An international collaboration between EPFL and the University of Glasgow has developed an advanced machine-learning algorithm for effectively detecting concealed manufacturing defects in wind turbine composite blades, prior to their deployment.
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