Throughout many industries, one of the most critical and influential driving forces over the last decade has been the development and distribution of innovative and ground-breaking IoT solutions. Enabling these solutions has led to the considerable onset of intelligent edge systems, which boost the integral ability to congregate and analyze data at rapid speeds, allowing users to benefit from real-time insights delivered through various operable, contextually-aware applications. As a result of this transformative impact, many vertical industrial sectors have utilized edge intelligence real-time monitoring to greatly improve operational reliability, diagnostic reports, and manufacturing efficiency.
Among these solutions is IOTech, an edge software company specializing in building and deploying vendor-neutral software, platforms, and tools. The company recently announced the availability of their industrial IoT solution, Edge Xpert 2.1, developed with members of the Linux Foundation‘s EdgeX Foundry community. The solution operates on the EdgeX Foundry platform’s redesigned architecture, includes new key features, and supports a host of new APIs that customers within vertical industries can utilize.
Keith Steele, IOTech founder and CEO, stated, “IOTech is proud to have played a leading role in the development of version 2 of the open-source EdgeX Foundry platform.” He continued, “This version of Edge Xpert is the first availability of our commercial product that brings this exciting technology to the wider industrial market. The growing IOTech customer base can now benefit from these new APIs and improved data flow that deliver many performance and scalability enhancements.”
Combining commercial support for the new EdgeX Foundry technology with key added-value features for commercial deployments, IOTech makes Edge Xpert suitable for deployment in large industrial systems. Thus, Edge Xpert has efficaciously deployed its technology in several industrial IoT solutions across vertical markets, including smart retail, manufacturing, telecommunication, building automation, smart energy, and petroleum.
Smart retail has been thoroughly modified by IoT and edge computing digital solutions, causing improvements that have drastically transformed the entire customer experience and impacted the bottom line. While leveraging various new technologies, edge computing effectively integrates IoT devices such as scanners and cameras to increase overall operational efficiency by collecting information about customer behavior which is then processed and acted upon by applications running on edge-based systems. IOTech’s Edge Xpert platform is key to creating successful smart retail services because of its ability to considerably minimize integration costs and time to market for IoT-enabled retail solutions by providing a future-proof and vendor-neutral open platform.
The launch of edge computing has greatly influenced the success of smart manufacturing. Its exceedingly valuable data gathered from sensors has led to far greater productivity throughout the supply chain. By turning these vast data sets into organized and actionable material, edge computing enables data analytics that can be useful in a variety of use cases, including:
- Equipment Protection
- Supply Chain Optimization
- Predictive Maintenance
- Security Measures
- Production Flow Monitoring and Optimization
Multi-Access Edge Computing (MEC) technology augments IoT technologies with the intelligence and analytical capabilities of edge computing to extend cloud computing capabilities to the edge of the radio access network. Integral to enabling IoT applications within the telecommunications industry, MEC provides real-time, high-bandwidth, and low-latency access to radio network resources. This solution meets the demands of applications requiring high Quality of Service (QoS), dramatically decreased latency caused by dense geographical distribution and the necessary support for mobility. IOTech’s Edge Xpert deployed on MEC servers would provide capabilities similar to a gateway node, aggregating the immense amount of data generated by IoT services on the open edge platform.
Edge software platforms combine multi-protocol connectivity and the ability to incorporate data from multiple sources, which can then be analyzed and used in automating workflow processes, improving energy, and refining operational efficiency. Currently widely deployed, edge computing has been integrated with IoT into an assortment of automation systems, including:
- Identifying Correlations Across Different Types of Data
- Energy Analysis
- Fault Detection
- Validation of Investment Results from Energy Saving Measures
As one of the most sophisticated industrial edge computing systems beneficiaries, smart energy systems integrate edge computing solutions for collecting, computing, and storing smart meter data before transmitting it to the cloud. Bridging the gap between the smart grid and the cloud, it is geographically distributed and overhauls cloud computing by offering advantageous capabilities, including responsive grid control resulting from reduced latency, increased privacy, and locality for smart grids. Essential in facilitating features for smart grids, IOTech’s Edge Xpert enables open managed platform APIs to support application sustainability and distributed edge intelligence allowing for smarter and more responsive systems.
Aiming to minimize unplanned downtime, adopting edge computing solutions such as IOTech’s Edge Xpert has been a staple of an industry-wide trend to hasten data collection and processing speeds. Traditionally, the network bandwidth limitations have been evident with offshore oil platforms generating around 1-2 TB of data every day, an amount that can take 12 days to transmit to a data center. Due to this, a large amount of useful data is wasted, and the chance of downtime is considerably heightened. Although expensive for any manufacturer, the petroleum industry particularly suffers from unwarranted downtime. According to an MIT Sloan study, this can become very expensive, costing as much as $25 million a day, with a typical midsize Liquefied Natural Gas (LNG) facility having difficulties roughly five times a year.
By employing this technology, organizations across vertical industries can improve profitability, growth, and longevity by enhancing their ability to acquire and use relevant data in their decision-making.