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How leveraging smart factories optimises products and operations for manufacturers

Internet of Things

The Internet of Mining Things PIC

The Internet of Mining Things delivers the next wave of productivity

Through IoT, this next level of optimisation can be achieved for a single mine or a federation of mines, rail and ports.  The Internet of Things (IoT) is increasing the connectedness of people and things on a scale that once was unimaginable.  The magnitude of this evolution is momentous with more than 80 billion Internet-connected devices projected to be in use in 2024, up from less than 20 billion in 2014. When we then couple the data produced, and processes involved, in the interaction of things-to-things and things with people what results is a powerful model upon which to drive the digitisation and transformation of companies, industries and whole nations. The ability to use standard Internet technologies, such as unmodified Ethernet, throughout, from the enterprise all the way down to individual field devices enables new levels in connectivity for people, processes, data and things, ultimately providing greater productivity, better utilisation of assets, and improved decision-making to industrial companies. According to Michael Boland, distinguished systems engineer at Cisco, “The IoT is connecting people in more relevant, valuable, and meaningful ways; delivering the right information to the right person or machine in real time. Data is being leveraged in more useful ways for better decision-making. It has applicability across all markets; private sector and governments.” The mining industry has a lot to gain from the connectivity that the IoT delivers. Mining operations around the world are on an automation curve – they are applying technologies processes to automate their key functions to gain efficiencies in production, however these initiatives are often focused and restricted within production silos. “We see a significant number of mines that have data locked away in individual systems but now want to federate that data together, instigate new processes, involving their people in new ways to achieve better […]

Smarter sensing PIC

Smarter sensing for the Internet of Things

In the picture:A test chip for a sensor node processor based on cognitive sensing technology. A 50-cent coin has been placed next to the chip for size comparison. A sensor node processor for networked sensor applications achieves ultra-low power consumption by using ultra-low voltage operation, hardware acceleration and cognitive sensing techniques. The Internet of Things (IoT) describes devices and applications that gather and distribute data for everyday life. Sensor devices and processes that will underpin the IoT need to be small, versatile and energy efficient. Now researchers at Agency for Science, Technology and Research (A*STAR) have developed a sensor processor node that is capable of intelligent sensing while using ultra-low levels of power. IoT applications range from biomedical signal processing to uses in vehicle-status monitoring and environmental sensing. Most IoT devices are tiny in size, which means that they typically consume only a small amount of power. This is particularly challenging for processors that sample the information from sensors and analyse the data, as their power demands, in contrast, are intense, explains Xin Liu and Jun Zhou from the research team. “The limits on the space for power sources such as batteries leads to a critical power budget at the level of the micro Watt,” says Liu. “At this level, processor design becomes extremely challenging if we are to achieve ultra-low power consumption whilst maintaining comprehensive functions.” Typically, the lower the operating voltage, the lower is the overall power consumption. The Institute of Microelectronics research team adopted ultra-low voltage circuitry and system design techniques, and further developed diverse hardware accelerators for high-energy efficient signal processing of sensor information. A further key advance is possible by taking a more intelligent approach to the signal acquisition, by utilizing the knowledge about the specific sensor signals. In many applications, sensor signals take the […]

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