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:
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 in IoT follows the typical Input > Process > Output cycle of any computer activity.
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.
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.
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.
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.
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.
Some of the factors that you must take care of while selecting the most suitable IoT platform include:
Here are some of the best tools and platforms being used for IoT data processing in 2019.
Google cloud provides multi-layered architecture suitable for organizing, managing, and sharing documents. It has AI/ML capabilities and provides real time business insights.
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.
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.
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 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 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.
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.
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
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.
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.
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.
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:
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.