A truly enhanced lifestyle is sneaking up on us very fast.
Your fridge will do your grocery shopping for you; your car will guide you through the best route or rather drive you through it, your house will protect itself and decide the temperature in each room, and your kids will play with a robot-dog which will act as your personal assistant too. Sounds like the Jetsons age, but that is just the beginning.
We are constantly coming across devices, which provide us with enhanced utility and flexibility in our day to day lives, which are gradually becoming a part of our routine. The current applications of IoT in our personal lives might be limited, but they are rapidly increasing in the manufacturing, industrial and to some extent in the healthcare sector.
Statista predicts the increase of IoT devices from 26.66 Billion in 2019 to 75.44 Billon in 2025, a span of just 6 years.
IDC Forecasts Worldwide Spending on the Internet of Things to Reach $745 Billion in 2019, Led by the Manufacturing, Consumer, Transportation, and Utilities Sectors.
These predictions, though appalling will cause immense pressure on the infrastructure and networking for them to be evolved to provide more horsepower and 24x7 uptime, all while reducing its size.
The Face of IoT in coming years
IoT is all about automating your routine, enabling access to a common hub of information via the Internet, learning and improving the processes and in turn, increasing the efficiency by reducing the energy spent on them; all this facilitated by devices with an aesthetic appearance of a conventional object.
Due to its promise of automation and improving efficiency, the manufacturing sector is foreseeing innovative implementations of IoT devices over the years to come. This will trigger a requirement for increased storage and processing power. The instinctive decision of most organizations is to build an on-premise IT infrastructure to support these devices. Either, firms can buy and maintain this infrastructure on their own or procure them from vendors who ensure, quality, availability, and maintenance of this infrastructure.
Here steps in, the Cloud. Cloud services are based on the ideology of hosting your applications on the infrastructure facilitated by third-party providers. In the above case, the firms can procure IaaS (Infrastructure as a Service) for their IoT needs. The Infrastructure provided by the Cloud services allows simple scalability. Hence, the customers can increase or decrease their demand for storage and processing power as per their needs and pay as per their usage.
With the increased use of mobile phones, Virtual Assistants, IoT enabled household devices like fridges, washing machines, security devices and many more, the customers are going to see a surge in the encroachment of IoT devices in their personal lives. These devices, while facilitating a comfortable and improved lifestyle to the customers, will also parallelly generate a mass of data that will have to be processed, stored, and converted into information relevant for business and analytical use. These devices, though intelligent, have limited processing and storage power and have to be in sync to provide an optimal service. It is easy for organizations to get overwhelmed with the amount of data that will be generated.
PAAS – (Platform as a service) in the current cloud computing scenario, is when a third party provider facilitates an underlying platform to run, develop or host your existing software. Big data is a field that deals with such proportions of datasets which are too large for traditional data processing. They aim towards extracting business-relevant information useful for predictive analytics. Hosting and maintaining Big data services is a costly and engaging affair. Hence, it is feasible for organizations that generate this kind of Big data to procure Platforms as a service from Cloud computing vendors which are relevant for Big data. This further allows the aggregation of Business Data and the data generated from IoT devices onto a single platform opening doors to more accurate predictive analytics, dependent on the real-time data.
Oracle Big Data Cloud, Big Data Analytics on the Google Cloud, Microsoft Azure and AWS are some of the leaders in providing Big Data platform services on the cloud.
Currently, the spread of these IoT devices is discreet, with individual firms contributing to the solutions based on their domains. Hence the underlying platforms for evaluating the direction and analyze these applications are segregated. But gradually there will be a need to standardize these underlying AI or Machine learning applications which are reusable and made reachable to the smallest of vendors. AI and Machine learning software must be fine-tuned to work as per your needs and the results that you need to gain from them. This is a collaborative task of applications from similar domains contributing their learnings together.
Software based on these applications can be made accessible to a larger audience, by hosting it like a service. SaaS allows even the smallest of vendors to use complex and predesigned software for their applications with a reduced cost at a monthly subscription fee. When multiple vendors accept and start contributing to its improvement, this will lead to standardization. The standardization of software used over devices paves the way for innovation, which leads to faster growth and development of the technology; and consequently, contributing to the quality of IoT services.
Data Lakes and Analytics by AWS provide Machine Learning and Analytics services over the AWS Cloud. Microsoft Azure Machine Learning Studio and IBM Watson ML Model Builder are a few tools hosted to provide MLaaS (Machine Learning as a Service).
Most IoT organizations are hesitant to move on the cloud due to the security concerns they foresee in having their confidential client data on an isolated location. But as the Cloud solutions are going large scale, their security teams are also expanding. They follow strict regulatory standards and security tools to protect their clouds, and in turn your data. Further clouds offer multiple strategies while hiring a cloud service.
Public Clouds have all hardware and network devices managed by the third-party cloud provider. The same hardware is shared with multiple organizations as cloud “tenants”, hence drastically reducing the costs.
On a Private cloud, the hardware is dedicated solely to your organization and the infrastructure is maintained on a private network. This makes it easier to meet certain IT regulations.
A Hybrid cloud is a mix of both the worlds. Here you can choose which of your applications should be hosted on a public cloud and the other on a private cloud, depending upon the privacy the domain demands. Hence, you can easily move your resources to and fro, from either of the clouds.
With these options at hand, you can choose what the requirement of your IoT application is, and which would be the correct cloud service for you to go to.
Cloud opens up an enormous playground for IoT enterprises to flex their applications and get the most out of their devices. Cloud computing services would not only enhance the reach of these devices but improve the security and quality of the services provided by it. The reduced costs will make them accessible to the smallest of the customers at affordable prices, hence opening the doors to a sea of opportunities ahead.
