Countless mines worldwide are already deploying autonomous driving mining vehicles to improve productivity and safety. In this post, we will review an autonomous driving vehicle solution that relies on different components, including in-vehicle computing, devices, networks, and the cloud.
Boats and ships traveling offshore usually have limited access to fast Internet connections. Without fast internet, they can’t benefit from what cloud computing has to offer, including data analytics and AI/ML technologies. But now, thanks to edge computing and improvements in wireless communications, the maritime industry is starting to introduce words like “smart” and “autonomous” into their dictionaries— you’ll now hear: smart boats, autonomous ships, etc.
Traffic systems rely on all kinds of sensors and IP cameras to gather real-time information from the field regarding traffic flows and congestions. Such information could be used to control traffic lights, information displays, video cameras, actuators, or simply to monitor traffic flows.
Intelligence (AI) and Machine Learning (ML) technology is undoubtedly the best path to efficient and precise autonomous driving systems but also one of the most challenging. The traditional in-vehicle technology doesn't have the necessary capacity to perform high processing workloads, especially intensive AI and ML decision-making.
Big-city transit for most urban populations is a way of life and with digitalization and state-of-the-art technology, metro systems can leverage analytical and decision support tools to reduce risk, improve service, and increase safety. Metro and other major public transport systems have embraced evolving digitalization for the provision of services such as security, customer service assistance, and operational support.
Commuter, subway, light rail, and high-speed passenger rail systems are popular modes of mass transportation and are particularly important for cities undergoing rapid urbanization. Rail system digitalization provides many advantages like automated train control (ATC), predictive maintenance, vehicle tracking, and automated fuel and fleet management to ensure maximum security, safety and efficiency of operations.
As public safety technologies continue to improve and evolve, mobile command and control center (MCCC) solutions are becoming more prevalent for public safety agencies of all sizes, and recognized by law-enforcement and military applications and even among organizations that require high quality, mobile video surveillance. Mobile command centers can be vital equipment during emergencies, man-made or natural disasters, enabling quick response and uninterrupted communications to monitor and respond to a crisis.