Wearable devices for tracking
IIoT Industrial Internet of Things (IIOT) is the subset of IoT wearables, targeted specifically at manufacturing industrial applications for employee tracking, patient tracking, visitor tracking, etc. The Industrial Internet of Things is about the interconnectivity of machine-to-machine, the sensor-transmitted data exchange, and its benefits to the smart factory/manufacturing industry. But, for this high-value equipment to be considered a part of the Industrial Internet of Things (IIOT) they need the capability to “communicate” with each other. Fortunately, industrial and technology companies such as Ripples IOT wearable solutions have been able to achieve this by creating Digital twin solutions that connect devices and allow them to “talk” using machine wearables for construction lone worker tracking, patient tracking, employee tracking for enhancing security, safety and productivity.
Wearable devices for worker tracking
The CEO of Intel, Brian Krzanich, was the first to use the term machine wearables for tracking when he referred to the practice of retrofitting industrial equipment with wireless sensors to track location and capture data about machine performance in real time. The sensor data is then used to identify equipment maintenance needs before they become breakdown issues, increase factory productivity, enhance the life of legacy manufacturing equipment, and lower costs. Although B2C IoT applications still addressing for 60% percent of the consumer wearables market, B2B industrial applications around condition monitoring are increasing annually giving rise to another IOT category – the Industrial Internet of Things (IIOT).
Wearable beacons for worker tracking
Incorporating Bluetooth mesh network technology within a shop floor can deliver considerable improvements in different aspects of their daily operations. Some ways in which businesses are using it include the following.
For instance, European aircraft maker Airbus has launched its “factory of the future” to streamline manufacturing operations, reduce human errors, and improve lone worker safety to comply with the industrial policy norms. This manufacturing plant is a digital one, with wireless sensors on high-value equipment and tools in the plant and manned by staff fitted with industrial machine wearable technology.
Proactive Maintenance: Indoor positioning beacons fitted on a high-value physical asset transmit information on how that piece of equipment is operating directly to a wireless exchange network from where it is interpreted into human and supervisory applicable information using data visualization tools. With time, this sensor data analysis reveals a pattern of events that are responsible for equipment failure (anomaly detection) and can warn the maintenance team of potential problems.).
Wearables for tracking maintenance & repair scheduled
A great advantage of this type of IoT assisted facilities management, preventive maintenance & repair planning becomes evident when one considers a warehousing business or manufacturing unit that owns hundreds or even thousands of high-value equipment. Imagine that in order to free up the maintenance team and allow them time to focus on mission-critical plant and machinery, such an enterprise concern decides to adopt Total Productive Maintenance or Predictive Maintenance using retrofit condition monitoring solutions.
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Wearables devices for industrial applications
The IOT is more common than you, shop floor managers, and maintenance teams may realize. For example, every time you access the camera from your smartphone you are using IOT. Essentially, the IOT retrofit kit works in a similar fashion but is developed specifically for factory assets and manufacturing plants. The sensors attached to your equipment communicate via wireless mesh that measures temperature, humidity, air quality, pressure, vibration, etc. The shop floor premise behind this setup is that smart factory machines which perform better than the smartest shop floor managers, at capturing, analyzing, and communicating large amounts of real-time data using machine wearables.