Azure Internet Of Things

1. Predictive Maintenance Internet Of Things An Internet of Things (IoT) strategy for predictive maintenance (PdM) need not be that different from any other operational technology strategy, or for that fact, any business-related strategy or implementation plan. These are the basic building blocks, stock phrases and truisms one finds in most of the business strategy literature. Develop new business models to uncover new revenue streams and new sources of value for customers.

3. Predictive Maintenance IOT These are the basic building blocks, stock phrases and truisms one finds in most of the business strategy literature. They are legitimate, unoriginal pieces of advice. None of it is contradictory or controversial, and these behaviors have been cited by those declaring success. IoT Planning Recommendations These are the crucial things to consider as you plan your foray into IoT-based predictive maintenance: • Obtain C-level buy-in before you start • Think globally, act locally • Go for low-hanging fruit to obtain the success and enthusiasm needed to obtain approval to achieve more expensive goals • Remember that no one vendor can do it all; pick those that have a track record or commitment to working together • Understand the value PdM will bring before you start

4. Always include change management activities into your plans • Understand which equipment is worth a predictive maintenance investment • Understand which equipment failures can be forecasted versus those that cannot Micorsoft IOT We are your digital business partner: part business consultants, part technology consultants. Mariner provides digital business enablement to aspiring mid-market companies. We have the experience and the skills to design, develop and execute digital business programs using our Microsoft Azure-based Digital Business Enablement Platform to accelerate your progress. Mariner is the nexus where business strategy converges with digital technology helping organizations to improve customer acquisition and retention, optimize business operations and create new business models.

5. Since our beginning in 1998, we have worked hard to positively affect the bottom line for customers we serve. Our holistic approach to business solutions means that we don’t just think in terms of today’s problem, technology or solution. We develop pathways for an organization to continue to evolve based on sound technology, a firm understanding of the company’s short and long-term goals and an appreciation for the company’s culture. Micorsoft IOT

6. Predictive Maintenance Internet Of Things IoT Implementation Suggestions Once the vision is clear, follow these recommendations to minimize risk and facilitate rapid payback from your IoT predictive maintenance investment: • Start small, then expand • Deliver iteratively • Avoid obscure standards • Choose popular technology backed by a solid name, but on their emerging, relative to your situation, platform. • Avoid technology lock-in • Ensure security is a priority for any IoT project and build depth as well as coverage • Start with telemetry before moving to control • Always include upgrade and configuration management requirements into your plans • Understand the warranty consequences of fitting sensors • Develop an archive strategy early • Embed the PdM into your standard workflows and operations

7. Microsoft Internet Of Things Beginning as an application development company in 1998, in 2001 we became business intelligence/analytics company. In 2013 we made another shift and now focus entirely on helping aspiring mid-market companies become digital business leaders using the additive capacities of the social, mobile, big data/analytics, decision management, Internet of Things, work management and cloud technologies. We specialize in helping mid-market companies improve customer experience, optimize business operations and create new business models and revenue streams. Today, we are a leading Microsoft Gold Partner, leading the charge to apply well-known and well-liked Microsoft technology to digital business strategies.

8. Azure Internet Of Things Our solution is a heavily modified version of a system described by Alan K Fish, in his book Knowledge Automation. The technologies used in our example include Microsoft Azure Machine Learning (ML), Azure Intelligent Systems Service (ISS), HDInsight, and Sparkling Logic’s SMARTS Decision Management service. We’ve applied our expertise in predictive maintenance (PdM), decision management, analytics, machine learning and cloud to create the conceptual architecture show below.

9. At the cost of oversimplification, here is the flow: Azure Internet Of Things Data is generated by various devices and sensors. Azure ISS is used to provide a secure connection and help with the management of devices and collection of data. Once the data is in the cloud we store it in a “data lake” built using HDInsight. Next we apply Azure ML’s machine learning algorithms to uncover patterns and gain predictive insight. Finally, the enriched data set can be fed to a decision management service, like SMARTS, which fires off decisions. In short, the architecture above siphons data in, makes sense of it and churns decisions out – with limited human involvement! While many details are missing, conceptually this represents a predictive, “decisioning,” cloud service that can be re-used for multiple scenarios.

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