Introduction

IoT stands for Internet of Things. It essentially means a network of devices and objects that are connected to the Internet. Being connected to the Internet means that they can either collect data and send it through the Internet, receive information from the Internet, or do both the things

All solutions in IoT typically involves four components – sensors, connectivity, data processing, and a user interface.

Sensors are objects that collect data and send it over the Internet. The data could be sent for storing, processing, or further dissemination of information.

Wired or wireless connectivity between the devices and processors is very essential, and is always through the Internet.

The amount of data collected by IoT devices is humongous. The amount of storage space as well as processing capacity required to utilize this data is also very huge. Cloud solutions for both storage and processing are proving to be a boon because they are:

• Affordable
• Scalable
• Fast response times
• Quick time to market

User interface in IoT solutions need not always be visual, which presents challenges to solution developers. Here user experience becomes more important and must be taken into account before any discussion on user interface can ensue.

All the four components of an IoT solution are important but data processing proves to be the most challenging as well as crucial.

Here we will look at how data processing works in IoT.

Data processing cycle

Data processing in IoT follows the typical Input > Process > Output cycle of any computer activity.

Input

For any processing to occur, input must be available. The data collected may be in the form of images, QR codes, text, numbers, or even videos. All these data must be converted into machine readable form before they can be sent for processing.

Process

This is the phase where the actual data processing happens. Different techniques like classification, sorting, calculations, etc. are used to get meaningful information from the data received.

Output

Although the information is produced in the processing phase itself, it is rendered into human readable format in the output stage. This output maybe in the form of text, graphs, tables, audio, video, etc. Output may also be stored as data for further processing at a later date. This is essential because comparison of current information with historical data can produce useful insights into the overall functioning of a system. This comparison can also be used to predict future behavior.

IoT platform

One advantage of using an emerging technology is that there are many options available to you, before some of them are deemed so successful that all other take a back seat. In business, where each problem is unique, availability of multiple options should always be encouraged.

Currently there are hundreds of IoT platforms available in the market. You should select the one ideal to you depending upon your unique challenges and the amount of time, resources, and money you are willing to put on it.

Typical IoT architecture

You must have knowledge about what a typical IoT architecture should comprise, before you can select the ideal platform for you. Any IoT architecture is a multi-layered structure that has different tools for performing different activities.

The first step in any IoT solution is data collection and your platform must provide multiple ways of doing this. The objects should be constantly connected so that critical data is not lost. The architecture should also take care of back-end management of these devices, including continuous software updates and remote device management.

Once the data is collected it needs to be converted from its analog form to digital so that it can be stored, processed, and analyzed for further action. You must confirm that the IoT platform provides a robust engine that can take care of all the rules to be applied for real time analysis of incoming data.

Storing the important data sets and the analytics is a crucial function of any IoT platform because it affects the action that must be taken as per the data collected.

Criteria for selecting an IoT platform

Some of the factors that you must take care of while selecting the most suitable IoT platform include:

• Suitability – The platform should be suitable for your unique business requirement. It would be ideal if the platform has been used previously for a similar use case.
• Stability – The platform that you are going to use must be stable under all circumstances most of the time.
• Scalability – One of the most important advantages of using IoT is the ability to scale up as per requirement. You should take care that your choice of platform does not hamper this in any way.
• Security – How secure are your processes? How secure is your data? how secure is the information provided by the users? These are some answers you must get before selecting a platform.
• Data ownership – You should never assume that since it’s your business you automatically own the data generated. Ensure that it’s you and not the service provider who owns the data.
• Pricing model – IoT platforms typically use cloud for storing, processing, and displaying information. The usual payment model is pay as you go. Understand the pricing model thoroughly, with its caveats and loopholes, to ensure that you do not end up paying much more than anticipated when you actually start to use.
• Performance – It is essential to enquire into the past performance of the platform. You want a nearly 100% up time for the platform so that your users do not face any glitches anytime.
• Additional tools – The platform should provide additional tools that your developers can use to create their own customized tools, apps, reports, and interfaces

Best Tools for IoT Data Processing

Here are some of the best tools and platforms being used for IoT data processing in 2019.

Google cloud

Google cloud provides multi-layered architecture suitable for organizing, managing, and sharing documents. It has AI/ML capabilities and provides real time business insights.

IBM Watson IoT

It allows businesses to collect, collate, and communicate data from smart devices, embedded machines, and wearables. It boasts of domain expertise that can be used to develop customized and flexible solutions. It is supposed to be highly secure platform in its price range.

Amazon AWS IoT Core

AWS from Amazon is a suite of software designed to provide end to end IoT solutions right from sensors, connectivity, data processing, storage, and user interface. It is a highly secure platform that can track and communicate even when your devices are not connected with the Internet.

Microsoft Azure IoT suite

The beauty of Microsoft Azure suite lies in its flexibility. It can be used to develop solutions for varied industries from health care, manufacturing, and retail to transportation, predictive maintenance, and smart connected spaces.

Oracle IoT

Oracle IoT cloud enables you to connect your devices to the cloud so that you can collect data, analyse them in real time, and relay them to enterprise applications as well as web services. It can be used to easily extend existing systems like retail management, supply chain management, human resource management, ERP, and customer handling.

Cisco IoT Cloud Connect

Cisco has stuck with its core competence of networking even while developing IoT cloud Connect, its mobility solution. It is designed to help mobile operators optimize their network, secure communication channels, and manage data effectively.

Emerging Use Cases for IoT Data Processing in IoT

Let us look at some of the most popular use cases for IoT data processing, areas that have been impacted the most through the use of IoT.

Use Case #1: Consumer Product Usage Analysis for Marketing

Whatever the technology, customer remains the king. Businesses are always looking at ways to get more information about the way a product is used by the consumer, so that further marketing strategies can be built around it. IoT has become a useful tool for these purposes. Data collected from smart devices enables them to understand how the consumer is using their product and create further marketing and new product launch strategies around them

Use Case #2: Serving Consumers and Business Users with the Same Analytics

The data collected by IoT devices can be used by both consumers and business users for their unique purposes if different analytics and interfaces are created for different set of users. For example, consumers can use data provided by smart coffee machines to monitor their coffee intake in a day. The same data can be used by coffee machine makers to analyze usage pattern and strategize for selling coffee machines as well as coffee capsules accordingly.

Use Case #3: Sensors and Cameras Enable Connected Events

As the concept of emotional selling is gaining momentum, businesses want to know what their consumers are thinking, and what is shaping their behaviour. Events connected via use of sensors, cameras, facial recognition, and social analytics are gaining popularity. Data provided during connected events enable them to identify the parts that were liked by the viewers and parts that were boring. This can be further used to decide which clips of the events should hit the social media sites and which should not, for maximum traction and visibility.

Use Case #4: Video Analytics for Surveillance and Safety

One of the most important areas where video analytics is being used is surveillance and safety of both indoor and outdoor spaces. This will enable availability of safe environments in schools, colleges, playgrounds, offices, shopping malls, and others public places. The live feed provided by video cameras can be monitored so that proactive safety measures are taken rather than reactive ones.

Pitfalls/challenges in data processing for IoT

Like every coin has two sides, every technology has advantages as well as disadvantages. Some of the challenges faced in data processing for IoT include:

• Handling volume of data generated: As discussed earlier, the amount of data generated by the sensors is humongous. As time, money, and effort are required to store and process this data, it is essential to confirm that generating such amount of data is necessary for the functioning of the system. Further, businesses also need to develop or purchase tools for handling the data generated. This requires allocation of budget as well as resources.
• Is cloud really secure: Although cloud has gained widespread acceptance, the jury is still out on whether cloud solutions are really safe and secure. As someone invested in using cloud solutions for storage and processing of IoT data, you must ensure that all the data and information stored on the cloud secure. The connection pathways between the sensors, storage devices, processors, and user interfaces must also be completely secure.
• Service level agreements: When you are entering into agreement with cloud service providers for availing their storage and/or processing solutions, you must look into the service level agreements minutely. You must be aware of all the services that they are supposed to provide, how secure their system is, how frequently their system is prone to breakdowns, and what are the provisions in case you wish to change cloud vendor.
• Lack of industry standard architecture: As discussed, there is no standard industry standard architecture for IoT solutions. You must ensure that the platform you have chosen is suitable for solving your problems, fulfilling business needs, and transforming your business to the next level.

Conclusion

IoT has utility across multiple industries like manufacturing, rutile, consumer goods, event management, social media, health care, energy conservation, etc. It is up to us how we embed intelligence in two devices and use them to collect data that can be used to make life better, transform businesses, and achieve growth. As discussed here, there are still many challenges to overcome before the potential of IoT can be fully utilized. But that should not stop anyone from using it in its current transformational stage to start getting benefited by IoT.