IoT enabling Technologies

The popularity and effect of IoT have made it an interesting topic of discussion for many people, companies and organizations. We have been exploring some of the interesting topics about the Internet of Things, and in this chapter, we shall be looking at those technologies that enable IoT to exist and function. Don’t forget, IoT is only operating because some devices are connected, communicating and sharing data. So, what makes all these possible? Let’s find out!


A sensor is a device which identifies any change that occurs in physical or electrical or some other quantities and immediately brings out an output to show the change. Sensors also send their output as an optical or electrical signal ( KITS & SOLUTIONS, 2019). Many of us use sensors daily without even knowing it. For instance, our television remote control uses IR sensor, shopping malls with automatic doors uses Passive Infrared sensors while street lighting and outdoor lighting uses LDR sensors. So you see that sensors are enabling technologies that help most devices to function as they should.

Now when it comes to IoT devices, sensors enable them to function properly. IoT combines communication network and sensors to share information amongst them thereby improving their functionality and effectiveness. Some sensors used in IoT are as follows:

  • Temperature sensors

These sensors detect physical temperature change from a source and produce the output which a user or other devices need to function. Some categories of sensors under temperature are Thermocouples, Resistor temperature detectors, Thermistors, Semiconductor, Infrared sensors, etc.

  • Proximity sensor

This sensor is used in IoT to detect whether a nearby object is present or absent. When this happens, the data is converted into a signal which a user can read and act upon.

  • Pressure sensor

This device senses when there is pressure and delivers output electrically.

  • Water quality sensor

Devices in IoT use this sensor to detect the quality of water and also facilitate the monitoring of Ion in distribution systems.

  • Chemical Sensor

Many industries use this sensor to monitor or discover when there is a change in air chemical.

  • Gas sensor

These sensors monitor the quality of the air and also indicate the presence of gases in the air.

Apart from the sensors mentioned above, other types used on the Internet of Things are a smoke sensor, IR sensors, level sensors, an image sensor, motion detection sensors, accelerometer sensors, gyroscope sensors, Humidity sensors, optical sensors, etc. One thing which is very clear is that without sensors, most of the functions of the IoT will not be possible (Sharma, 2010-2019).

Embedded Systems

In this era, almost every electronic component comes with an embedded system that helps them to carry out some specific tasks. These systems are unique because they require low power to carry out their functions. Some vices we use such as washing machines, RFID tags, remote controls, sensors, thermostats, microwave oven, routers, mobile phones, modems, PDAs, use embedded systems to enable them to function properly (INFORCE, 2017).

From the explanation above, it can be understood that embedded systems are attached to large devices, and they perform a specific task for such devices. In chapter one, we explained that many devices that are not qualified to be a part of IoT could be enhanced with the help of embedded systems. What it means is that when an everyday device is manufactured with such a system, it can help it to perform other specific tasks which it wasn’t able to do.

So, without embedded systems, IoT may still be a myth because, if the devices we use have no way of connecting or participating in the machine to machine communication, the importance of the Internet of Things will not be felt. Furthermore, the utilization of many IoT solutions relies heavily on embedded systems especially in the area of industrial IoT applications and verticals (Mind Commerce Staff, 2015).

Big Data and Data Analytics

We already know that the Internet of Things has to do with the activities and communications of connected devices that generate and share data amongst them. These devices collect data and transfer the same via the Internet using embedded technology.

Big Data is the large set of unstructured, structured or semi-structured data which are analyzed to get insight on business trends. The question is what happens to the large data that are accumulated during the process? That is where big data comes into the picture.

The Internet of Things generates these data, and without them, businesses will not have the resources to equip themselves with decision-making tools. However, the data in its raw form will not be beneficial if there is no analysis of them to identify patterns and trends. So what is the next best thing that can happen? Data analytics tools are used on them to get the necessary information for big industrial shots to take the best decisions (Verma, 2018).

Data analytics turns the data generated by the Internet of Things into something that can be useful. DA is that process which analysts use to examine both small and big datasets with different data properties to bring out actionable insights and meaningful conclusions. The conclusions extracted by data analytics come in the form of patterns, trends, and statistics which helps businesses to be proactive in their decision-making processes (Joseph, 2018).

Cloud Computing

Cloud computing which we usually call “the Cloud” is a technology which stores data, delivers data, photos, applications, videos and other things over the Internet to many data centers. According to IBM, cloud computing has six categories, namely, Software as a service (SaaS), Platform as a service (PaaS), Infrastructure as a service (IaaS), Public Cloud, Hybrid Cloud, and Private Cloud.

On the other hand, IoT is home to connected devices that work every day to make our lives easier and simpler. Cloud computing works in the same way to ensure that data gets to users without any hitch. So, the Cloud is another technology that ensures the proper functioning of the Internet of Things. You may ask how and the answer is simple.

While the Internet of Things generates large quantities of data, it is the role of the Cloud to provide the pathway through which the data gets to its rightful destination. Therefore, it is safe to say that without the Cloud, data may not get to where they are needed (STONEFLY, 2018).

Machine Learning

Machine Learning is that branch of Computer science which focuses on teaching computers/machines how to learn on their own using available data. ML enables machines to learn without human intervention. Even as humans learn through experience, machines study and analyze system behaviors and output data and take decisions based on the analysis. How does Machine Learning technology affect or influence the operations of the Internet of Things?

IoT generates a massive amount of data, and this data comes from machine to machine communication. Machine Learning techniques and algorithms enable the analysis of these data in such a fast manner as required by IoT devices to communicate. Some of the ML techniques for IoT data analysis are decision trees, neural, clustering and Bayesian networks. These techniques help the connected devices to identify patterns re-occurring in multiple streams of data from different sources. After identifying these patterns, the devices can now take the right decision based on the result of their analysis.

From what we have explained, it is clear that Machine Learning enables IoT devices for analyzing data without coding or programming. Therefore, if you remove ML from IoT, the functioning capacities of the latter will be limited since the smart devices may not make decisions as required in real-time (Ratan, 2018).

Semantic web

Semantic Web is an extension of the World Wide Web that concentrates mostly on data. It serves as a platform through which data can be shared and re-used across many applications, community boundaries and enterprises. The Semantic Web is therefore considered as an integrator across diverse content, systems and information applications (WIKIPEDIA The Free Encyclopedia, 2019).

Semantic Web technologies help to model data and also integrate data accumulated from diverse sources over the Internet. Since IoT devices generate heterogeneous data, which hinders interoperability between its applications, the need for Semantic Web becomes necessary. Semantically annotating Internet of Things data will help to develop inter operable and smarter IoT (ScienceDirect, 2017).

Blockchain and Cyber Security

One of the reservations which people have about IoT is the security of the connected devices and data which they share. Due to the nature of the IoT market which is largely unregulated, it is possible for hackers to have a field day playing with people’s information. Although IoT has many options when it comes to upgrading its security needs, Blockchain is at the forefront. This technology serves as a distributed ledger where data transactions and records are kept in blocks. Also, blockchain is decentralized thereby preventing the authority of a central body or administrator. Further, this tech uses cryptography algorithms which helps in preventing data distortion and also enhances security (Mcgrath, 2018).

Blockchain can protect IoT devices from data tampering; enable the locking of unauthorized access to IoT devices and shutting down compromised devices (IEEE Innovation At Work, 2019). Also, if the IoT network is decentralized, security challenges will be solved. Since the Blockchain tech is known for autonomy, decentralization, trustworthiness, and scalability, IoT can also benefit from these capabilities.

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