ABC faced two major issues when utilizing the data collected. One is the size, complexity, and disparity of the data collected would take lot of man-hours to process and evaluate. Two is real-time data cannot be put into use due to the nature of data science analysis.

Previously to working with ThingWorx, DeviceLynk built an IIoT platform but found it lacked scalability. They needed something to capture and handle data from an unlimited amount of devices and customers.

OnFarm needed to move quickly to capitalize on a significant "smart agriculture" opportunity to build connected applications and dashboards that captured and monitored sensors in the field and provided actionable data back to their customers. The overall solution OnFarm determined necessary was a set of "dashboard-driven connected services utilizing an IoT backend" that would accomplish several key things: • Easily collect data from incompatible sensors via wireless networks • Provide a means to integrate, analyze, and correlate different data sets of information into easily-understood and easy-to-customize reports leading to specific actionable outcomes • Manage end-user permissions, distribute reports and business intelligence through a customizable Web interface that would include dashboards, allowing custom organization of data applicable to the business employing OnFarm's suite of services

IOTATOI is a division of Power Agent Systems that has developed an edge server called the Universal Monitoring System (UMS). IOTATOI is using UMS as an edge tier data collector to monitor backup battery arrays in manufacturing, mines, and chemical plants. This experience with battery backups led IOTATOI to expand the system to any condition that can be monitored by sensors such as vibration, heat, temperature, and flow. IOTATOI found they needed to move from their original middleware to something that would allow greater scalability and to also present information in a much broader way allowing them to dynamically look at the information and perform benchmarking analysis, feeding the data into analytics engines and creating a much more actionable view.

The client had limited or inefficient integration of its data sources, which made it difficult to see patients through a longitudinal lens. The client was, however, uniquely positioned to leverage the expansive patient data contained within its network of care, and set out to do so in 2012. Specifically, they wanted to improve the outcomes of patients with Ischemic Heart Disease (IHD) through improved care management with goals of reducing readmission rates, better managing patient cholesterol levels, and better managing patient blood pressure. Specifically, the regional healthcare provider was interested in implementing a machine learning platform, that quickly automates complex analytical processes and integrates powerful information into existing applications and portals.

Taking advantage of the fast growth of China and the growing demands in embedded computer systems, Vantron technology was established in 2002 by Silicon Valley professionals and headquartered in Chengdu, China. In addition to readyto-run low-power embedded systems, Vantron also provides assistance in application software development, tailoring its embedded systems based on customers’ requirements, and offering turn-key manufacturing services. With customers in industries such as healthcare, heavy equipment, vehicle tracking and telematics, looking for customized solutions, Vantron saw more and more customers looking for interconnectivity through the cloud so that they could access and interact with their equipment remotely