Abstract

Root-cause analysis and gaining insight of the operations of manufacturing machines requires periodic measurements. Today, most such measurements are taken manually and are therefore not fine-grained, accurate, or fast enough for the smart solutions required by Industry 4.0. Such smart solutions are expected to use measurements from IoT sensors to make optimal decisions via data analytics, for instance, to perform continuous structural health monitoring [1], to enable smart manufacturing systems [2], to facilitate smart transportation [3], and many more. All of these systems need continuous feed of measurements from sensors, and very often the collected measurements are transmitted and stored in the cloud for data analysis [4]. Thus, not only the communication between the devices must be reliable, but also connection reliability to the cloud is equally important. In addition to that, the trend of data collection has become such that today, data is being collected before the precise needs of the data are known, so naturally, the best strategy is to store all of the data for possible future use [5]. This leads to a large amount of data, and considering that over the course of time more and more sensors will be deployed in an IoT environment, and more measurements will be generated, we can see that conventional networking approaches will not be able to cope with this huge demand. Smart systems, which need to be scalable, agile and fluid, are already forcing changes to conventional web technology to accommodate the volume, velocity and variety of measurements data generated from IoT [6].

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.