Along with the rapid evolvement of various portable electronic devices, smart home appliances and technological equipment, the internet of things keeps gaining critical importance and significant control. Because of its value and a powerful influence on our way of life, it has even been nicknamed the Next Industrial Revolution. Indeed, our habits and behavior have changed as the internet’s ubiquitous presence in day-to-day operations has simplified them tremendously. If this trend continues, what will be the internet of things in 2020?
What Is IoT?
To understand why IoT affects our lives so much and why it is one of the main data suppliers in information technology, we first need to understand its specifics. This methodology describes the connection and interaction among multiple devices equipped with embedded technologies. This umbrella term refers to a wide range of appliances that can be connected to the internet and concern the following physical areas:
- Smart homes
- Smart cities
- Banking and finance
As we see, the concept has entered many key domains and gained its foothold in multiple engineering operations. What are the reasons that the methodology is gathering steam, and more and more companies opt for internet-connected devices? Here are some of them:
- Increased efficiency. Information technology automates billions of operations, facilitating them and increasing their output.
- Decreased risk of errors. The connection among devices narrows down people’s involvement in the majority of operations, which reduces the risk of an error and minimizes the consequences of the human factor involvement.
- Better financial performance. The direct intercommunication among technological appliances eliminates some roles and processes to cut costs on their provision. At the same time, the increased operation efficiency results in the bigger gain.
- Better analytics. An overall coverage of all important activities and operations with analytics-capable appliances gives a clear overall picture, which improves the decision-making and issue-revealing processes.
However, the all-around devices’ connection to the internet cannot but cause certain challenges, such as:
- Threatened security. The more devices are on a network, the weaker the system’s security, as it becomes more difficult to monitor it and manage. This may cause gaps through which a system can be hacked.
- Compromised privacy. As billions of users’ personal devices and enterprises’ equipment are connected to the internet, there is a possibility of ownership erosion.
- Data storage. The amount of data increases, so it indispensably requires a sufficient place to store it.
- Personnel training. The introduction of new appliances and technologies demands their proper administration, so it raises a need in employees’ ongoing training.
- Resistance to implement IoT. People’s habitual reliance on themselves rather than on devices that can get out of order can cause resistance in incorporating IoT into both personal and business operations.
The infographic that illustrates it is below:
IoT and Data Creation
We can see that in less than 20 years, the internet of things has made a huge leap. It provides ever-growing market opportunities, and we can be sure that more drastic changes are yet to come. Fabrizio Biscotti, Research Vice President at Gartner, said: “Processing large quantities of IoT data in real time will increase as a proportion of workloads of data centers, leaving providers facing new security, capacity and analytics challenges”.
As IoT gets more involved in various domains and types of operations, a countless number of its data sources generate immense volumes of data. All the sources can be roughly divided into three groups:
- Passive sources. They are sensors that do not communicate actively and send the required information to the centralized management system only on demand. For instance, sensors that make atmospheric measurements produce data when API is activated. That does not mean that an app is also passive; on the contrary, the data from passive sensors requires proper management and processing, and it is what an application is purposed for.
- Active sources. The main difference between passive and active sensors is that the latter transmit data continuously, not only by request. An example is jet engine sensors. Information comes in a real-time manner, which demands an app to provide its ongoing processing. As the data must be safe, the application must parse it from the stream and then place into a proper format for storage and processing.
- Dynamic sources. These sources are most sophisticated, and also most useful ones. Devices with dynamic sensors interact with respective applications bidirectionally and perform a wide range of capabilities, such as data format and frequency change, security issue fixing, update automation and more. Also, they are auto- and self-tuned. Dynamic sensors do not just produce rough information to an app that processes it but can also send ready data that meets the app’s requirements. It is like the communication of an application with another one.
The emergence of new information sources indispensably affects the data center market, and it has experienced structural changes in recent years. Indeed, information technology tends to shy away from processing data in traditional data centers in favor of cloud ones. In just a few years, only 8% of overall workloads will be handled by old-school data centers.
Internet of Things by 2020
Numerous IT experts consider that the future of the internet of things is promising as it offers significant opportunities to businesses. Extensive funds are invested in the development of internet-connected devices. According to Gartner, 6,381.8 million devices were connected to the internet at the beginning of 2017, and this number is predicted to reach 20.8 billion by 2020.
Despite their wide variety, they all fall into three groups:
- Consumer devices
- Cross-industry business devices
- Vertical-specific business appliances
In 2015, Jim Tully, a then-VP distinguished analyst and Gartner associate, predicted: “Aside from connected cars, consumer uses will continue to account for the greatest number of connected things, while enterprise will account for the largest spending”. The statistics on the number of IoT devices are in the table compiled by Gartner analysts:
IoT Units Installed Base by Category (Millions of Units)
Source: Gartner (January 2017)
Following this dynamic, we can see that the compound annual growth rate of the number of installed devices is 26.18%. Such an upsurge cannot go unaccompanied; it will inevitably bring about the scaling up of the data generated by these units. As we can see from the table, the prevailing number of devices are those that serve consumer needs, such as smart watches, TVs and more. Also, there is a growing trend of cross-industry data sources taking over from the vertical-specific ones.
As the growing number of devices demands proper spending, it is estimated that investments into IoT will reach approximately $3 trillion by 2020, with a dominant share of application development and device hardware. As a comparison, total spending in 2016 accounted for $1.380 trillion, so it is going to increase more than twofold.
Consumer data source share in the overall number of devices that use IoT technologies accounts for 62% in 2017, and is likely to stay unaltered by 2020. Despite their prevalence over the business-type ones, spending on them still lags behind that on business appliances, as the following table shows:
IoT Endpoint Spending by Category (Millions of Dollars)
Source: Gartner (January 2017)
IoT not only changes the scale and variety of data but it also affects the quantity, which grows proportionally with the number of sources, aka installed internet-connected devices. According to expert forecasts, smart devices will produce one-tenth of the total amount of information on Earth, up to 44 ZB in 2020.
As cloud technologies are intertwined with the internet of things, cloud workloads will face a 3.7-fold leap from current 3.9 ZB to 14.1 ZB by 2020. Sixty-eight percent of cloud traffic will belong to public data centers. Also, figures show that cloud workloads will still be divided among platform-as-a-service (PaaS), infrastructure-as-a-service (IaaS) and software-as-a-service (SaaS) with their respective shares of the total cloud workload of 9%, 17% and 74%. IaaS will lose its ground, while the other two groups will ratchet up.
A soaring data volume inevitably leads to a growing demand for traffic storage. Consumer cloud storage will also see an increase by 2020: users will enjoy 1.7 GB every month instead of current 513 MB. Although it seems as if it may cause the data storage crisis, it is unlikely, as most data is transient and does not require permanent storage.
Concerning the data generation market, it will change significantly within the next few years. US, Germany and Japan – who now generate 60% of the total data – will no longer be leaders in 2020, as they will surrender to emerging markets, such as China, Russia, Brazil, India and Mexico.
In the future, the range of data sources will increase drastically, and further technological progress, process virtualization and automatization will only encourage it. Collectively, these data sources will generate even bigger amounts of information, and its volume will keep growing.
A great variety of IoT’s data sources and network connections threatens to create huge amounts of input data around the globe. However, the processing of the data in a single location is economically and technically inefficient, which triggered the emergence of centralized applications for proper data manipulation. This, together with an ever-growing information scope, factors into the development of efficient platforms for system management.