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Internet of Things

Your business is constantly generating data, which often remains unanalyzed and underutilized. Internet of Things (IoT) technology enables the creation, understanding and usability of your industry data at vast scales

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Infosmart Software is uniquely capable of guiding you through the wonderland of IoT. As an IoT consulting firm, we can prove the value of IoT specifically for your operations and validate how those benefits will continue. From simple conversations to early-stage demonstrations of the tech to proof-of-concept prototypes, we’ll advise you through the entire process. Utilize our staff on a per-project basis, or through staff augmentation under your team’s direction.

The Internet of Things (IoT) is the access of physical things to virtual technology platforms. When Objects can sense and communicate, it changes drastically how decisions are made. When more data can be gathered from wider ranges of places - and at a faster pace, businesses can increase product development, improve efficiency and enhance customer experience. IoT can provide all this and more.

Infosmart does IoT consulting and has a deep knowledge of IoT cellular technologies and solutions design, having pioneered the space since 2009. Countless companies are starting to explore IoT and the many possibilities that are associated with this innovative step in technology. The digital universe is expanding, and no longer do you need a human manning all business aspects to save you money. IoT is connecting millions of “unconnected things” to the Internet, allowing you to track and analyze date that wasn’t available before.

The space between the physical and digital spheres is fast diminishing in today’s hyper-connected world, spawning an era of true convergence, driven in part by the rapid proliferation of the Internet of Things (IoT). Companies are increasingly tapping IoT Solutions and Services to boost operational efficiency and transform their business models.

  • A partner in your IoT strategy development - we will help design and document a clear IoT strategy for your business
  • Thorough review of your business processes and painpoints A recommendation of end-to-end solutions that would benefit your company, along with transparent pricing
  • Expertise on the IoT marketplace as well as products and services for your Industry, we will help you stay competitive
  • Detailed write-up of your strategy, products and services, and a partner through the implementation process

We have several focus areas for IoT Consulting including Smart Manufacturing, Smart Buildings, Energy Management and Smart Cities. As an example, many cities are starting their IoT strategy, learning about available products and services and envisioning the future for their citizens.Some are starting small with parking solutions, more intelligent street cameras, led lighting, smart trash cans, and city-wide WiFi hotspots. Other cities are planning for autonomous drivers, fiber optic infrastructure, narrowband, car sharing, smart campuses and hospitals, and utilizing IoT for law enforcement. Our expertise gives us a deep understanding of these areas and how to apply them to your business, building or city.

Internet of Things can provide you Smart factory warehousing applications, connected logistics, industrial smart security systems, remote and predictive maintenance, energy consumption optimization

IoT provides more service lives compared to independent devices. The internet will disappear as we immerse our environment into it, it will be everywhere that it becomes part of us. As Internet of Things becomes more of a reality at many industries, knowing more about the technologies and processes of Internet of Things can position you as a top resource for your customers.

Smart home connected devices provide home owners with a better level of safety, security, convenience, and energy usage than a traditional non-connected home. Smart devices provide not only remote 24×7 monitoring of the home, but also offer immediate notification of events, enable control of devices while at home or away, and allow automated scheduling of devices to improve both convenience and energy efficiency.

Predictive Analytics

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The pace of digital transformation is increasing every year. One of key drivers of this acceleration is the vast potential of the Internet of Things (IoT).

The amounts of data sourced today from various connected devices every second far surpass the wildest dreams that businesses have had less than a decade ago. How to gather data is no longer the main question. The key challenge now is how to efficiently collect, analyze and convert data into actionable insights.

The Industrial Internet of Things (IIoT) is a segment of Internet of Things (IoT) that's often less visible than our common household objects such as cars, appliances, and central climate control that can be monitored and controlled by computers or smartphones. Dubbed the "fourth industrial revolution" or Industry 4.0, the IIoT is the digitization of industrial assets and processes that connects products, machines, services, locations/sites to workers, managers, suppliers, and partners.

In addition, the convergence of robotics, artificial intelligence, and big data analytics creates a potential for huge advances in productivity, efficiency, and cost savings. The IIoT creates a universe of sensors that enables an accelerated deep learning of existing operations. These data tools allow for rapid contextualization, automatic pattern, and trend detection. Furthering this for manufacturing operations will finally allow for true quantitative capture of formerly “expert” qualitative operations.

With machine learning, we want to extend our subject matter expertise to illustrate the predictive band even further. Polynomial regression fits a nonlinear relationship between the value of x and the corresponding conditional mean, and has been used to describe nonlinear phenomena such as the fault rate of bearings where x is time and y is ultrasonic vibration measured in G’s. This type of regression is used for the upper limit of the confidence band and matched best with our data and domain expertise mapping back to the hockey stick or nonlinear failure and conservative approach to ensure no underestimation or underfit model. The lower limit of the confidence band was estimated using simple linear regression.

Providing more feedback over time will improve the model, considering particular industrial machines in particular environments with more data. This will give plants and manufacturers more time to react to potential machine failures resulting in reduced unplanned downtime, more productivity, more cost savings on equipment, and improved worker safety.

Data and Analytics will be the key differentiator for IoT.

A single sensor collecting data at one-second intervals will generate 31.5 million datapoints year (source Intel/WindRiver). However, the value lies not just in one sensor’s datapoints – but rather the collective intelligence gleaned for thousands (indeed millions) of sensors working together

As I discuss below, this information (and more specifically the rate of IoT based sensor information and its real time nature) will make a key difference for IoT and Predictive analytics.

IoT and predictive analytics will change the nature of decision making and will change the competitive landscape of industries. Industries will have to make thousands of decisions in near real-time. With predictive analytics, each decision will improve the model for subsequent decisions (also in near real time). We will recognize patterns, make adjustments and improve performance based on data from multiple people and sensors

IoT and Predictive analytics will enable devices to identify, diagnose and report issues more precisely and quickly as they occur. This will create a ‘closed loop’ model where the Predictive model improves with experience. We will thus go from identifying patterns to making predictions – all in real time

However, the road to this vision is not quite straight forward. The two worlds of IoT and Predictive analytics do not meet easily

Predictive analytics needs the model to be trained before the model makes a prediction. Creating a model and updating it on a continuous real-time basis with streaming IoT data is a complex challenge. Also, it does not fit in the traditional model of map reduce and it’s inherently batch processing nature. This challenge is being addressed already (Moving Hadoop beyond batch processing and MapReduce) but will become increasingly central as IoT becomes mainstream.

Preventive Maintenance (IOT)

Problem

  • Due to the high-risk nature of manufacturing operations, the only solution for never fail situations has been to over-ensure uptime with redundant equipment and too many parts on hand—an unsustainable model.
  • While these systems track performance of various components using sensors, there’s typically no proactive way to trigger maintenance to avoid downtime.

Solution

  • This solution leverages Google Cloud Platform IoT core to read sensory data and predict the Remaining Useful Life (RUL) of components
  • Offers an end to end solution that securely reads sensor data in real time, processes the data and executes a Machine Learning model to get predictions

Benefits

  • Operations teams can plan preventive or corrective maintenance based on a deep understanding of asset performance patterns.
  • Proactive alerts help prevent costly downtime of machines