It may be the biggest buzzword of 2015. The Internet of Things has been discussed in just about every type of popular media, and in the world of IT; it is projected to be one of the largest areas of new spending this year. Of course, machine to machine communication is nothing new. But the accelerated pace of innovation and development in big data and analytics software has opened up a new universe of possibilities for connected devices. And that’s what makes the potential of IoT so exciting to so many people.

But along with these new possibilities come a new set of challenges. The very nature of IoT is to monitor, upload and act upon data from what are often complex entities.  Consider the examples of manufacturing and healthcare, in which a large number of sensors are continually uploading data that needs to be analyzed and acted upon to improve outcomes. Whether it’s predicting equipment failure or hospital readmissions, there are multiple parameters of information that are being monitored and analyzed, data that changes every second or even multiple times a second. 

In order to successfully implement IoT initiatives, organizations need to be prepared to address three primary challenges: 

1) The vast volumes of information that need to be uploaded from sensors to the central monitoring system.

2) The need to rapidly consume continually changing information in near real-time to gain an accurate understanding of what’s happening in the moment. 

3) The ability to not only understand historical data, but to anticipate and predict what will happen next to prevent or facilitate certain outcomes.

Predixion Software is uniquely positioned to help organizations overcome these challenges to achieve highly effective and adaptive IoT implementations. Unlike traditional analytic software that generates a mathematical model as the end result of its processes, Predixion focuses on making the results operational at the point of impact. In other words, Predixion transforms data science and real-time analytics into an action or decision on the spot. 

That’s a critical capability for any IoT initiative. Bringing an action “close to the edge” where sensors and data meet is the ultimate payoff of IoT.

Predixion calls this focus “the last mile of analytics” – delivering predictive insights directly to the agents of decision-making. That may be a nursing supervisor who needs to improve patient outcomes. Or an engineer who needs to predict equipment failure before it happens. 

For IoT, it means making decisions on the edge. Decisions that sometimes may not involve human interaction at all. Predixion is able to generate these analytical-based decisions and actions instantly in IoT devices, without the latency of uploading data to a cloud or a centralized processing environment. Pushing decision-making to the sensors in this way reduces the amount of data that has to be uploaded and relieves the pressure on server processing. 

For example, imagine a huge underground drill boring deep inside a mountain. In such an environment, there may be no Internet connection or enough time to analyze sensor data to predict that an equipment failure is about to occur. Predixion is able to embed the action to stop drilling before a failure occurs directly within the sensor. Preventative action is taken in near real-time. 

Predixion’s patent-pending MLSM (Machine Learning Semantic Model) allows data scientists and subject matter experts to collaborate and rapidly create, adapt and improve predictive models for specific IoT applications. The MLSM streamlines and simplifies this process, eliminating the need to understand the inner workings of machine learning such as shaping, managing and transforming data. 

Predixion also allows developers to build predictive models with a variety of tools including analysis services from Microsoft, Mahout, and R. Predixion can also consume predictive models built on other platforms such as SAS and SPSS via the PMML (Predictive Model Markup Language).  In order to serve the widest variety of IoT sensors, Predixion analytical packages can be wrapped into an OSGI (Open Service Gateway Initiative) bundle that runs on any device that supports Java. 

From beginning to end, Predixion offers a superior ability to create, collaborate, deploy and continually improve the predictive analytics that make IoT possible. It’s the most direct path for organizations that need to overcome IoT challenges and push ever closer to the edge.