The term Internet of Things (IoT) was first introduced in 1999 by Kevin Ashton in the RFID Journal. Later, the International Telecommunication Union (ITU) came up with a unique idea for connectivity among the devices: Anyone will be able to have connectivity with anything (device to device or human to device) at any time or any place (with any other device or device in commute). In the past, when this idea was discussed in the industry, the whole idea did not seem realistic to them. However ITU and small business ventures incorporated some sensors into the devices to make everyone see the evolution of the internet along with the combination of technology and vision. This new vision has the ability to change our day-to-day life forever. This is one of the biggest reasons why IoT products and their associated services will become popular in the society. IoT will greatly impact every part of the life – work, home, and social [1].
The definition of IoT is perceived differently, as many researchers have different ideas about IoT. Because of the different definitions, it has become truly difficult to comprehend the exact definition of IoT. On the same lines, many scientists, researchers, and standardization bodies are working on it but from their own perspective. This is creating more perspectives in addition to what is present right now. A combination of these merged perspectives from the abovementioned bodies can help us understand IoT and its ecosystem. IoT can be partitioned into three different dimensions on the basis of multiple visions:
1.The first dimension consists of things which include key chains, portable medical devices, or watches.
2.The second dimension is internet or connectivity-oriented dimension. This includes communication and connectivity among things.
3.The third dimension is semantic. It means data collected by various devices should be provided with some sort of technology in order to store, collect, sort and interpret that data.
The things can be further partitioned into different categories. Day-to-day objects like books, wallets, and carts can be connected to sensors, such as a temperature sensor and motion sensor. The others can be combined with appliances like a refrigerator or air conditioner. Sensors have been in use for a long time, but its connection with IoT can be helpful. When the term IoT is referred, it means connectivity among devices without human intervention. A vast amount of literature is available on IoT, but the difference in their perspectives causes confusion.
1.1.1 Technical Building Blocks
In the following section, the taxonomy of IoT components is presented. There are three main components of IoT [2,3]:
1.Hardware, which consists of sensors and actuators
2.Middleware, which is provided for the purpose of data analysis
3.Presentation, which is visualization of information made easy with the help of this layer.
Hardware, that is sensors and actuators, are the main components of IoT. Sensors are used to collect information on parameters like temperature, pressure, or humidity. Actuators are programmed to take action based on the value sensed by the sensors. These sensors can communicate through various wireless communication technologies like radio frequency identification (RFID), WiFi, and Bluetooth. These sensors need to have unique identification to be deployed in IoT application. WSN is the basic network in IoT. Data sensed by these sensors are stored and processed using Cloud computing. A few technical building blocks of IoT are discussed as follows:
1.1.1.1 Radio Frequency Identification (RFID)
RFID is one of the technologies which can be embedded into the microchip and can be used in wireless communication. Identification of the things that are attached to it is a major task. There are two types of RFIDs:
1.Active RFID: This RFID is powered. It means that it has its own power source. It can also communicate if necessary. Monitoring of valuable cargos is achieved by the active RFID tags.
2.Passive RFID: This RFID does not use battery. It makes use of readers’ signal to identify the ID for the RFID reader. The application of this RFID can be seen in retail, transportation, access control etc. These tags are used in various applications like road toll, banking cards etc.
1.1.1.2 Wireless Sensor Networks (WSN)
WSN consists of a number of intelligent sensors. These sensors continuously gather information after which processing is done on the collected data. The pre-processed data is used for analysis so that valuable information can be extracted from the collected data. Active RFID and lower end WSN nodes serve the same purpose in terms of processing capability and storage. The challenges that come with WSN are multidisciplinary in nature and so is the potential of this kind of network. Sensor data that is gathered from sensors is sent to the centralized or distributed systems for analysis. Recent advancements in technology have made this wireless communication very easy.
1.1.1.3 Addressing Schemes
Any IoT system should be able to uniquely identify things. This step is very crucial in making that IoT system a success. This will help in identification of billions of devices uniquely. Also, the management of these devices with the help of internet will be possible. A major critical aspect of creating a unique address is as follows:
- Uniqueness of address
- Reliability
- Persistence
- Scalability
Every “thing” that is connected in the system and those that are going to join should have a unique address, location, identity, and functionality. Currently the IPV4 addressing scheme is being used, but as the number of the devices increases, it becomes impossible for IPV4 to give unique ID’s to each and every device. The solution to this problem is the IPV6 addressing scheme. However, this will only solve the problem to some extent. The heterogeneity of the devices, their associated data types, and the operations on them still remains a major concern. In order to channel the data traffic ubiquitously and relentlessly, persistent network functioning can be used. Even if the TCP/IP is taking care of the efficient delivery from source to destination, IoT is still facing a bottleneck at the interface of the gateway and the sensors. Scalability of the available address should be sustainable. If at all another network is required to join in, then the performance of the existing network should not be hampered in any way. To solve these problems, Uniform Resource Name (URN) system was developed, which is being considered as the base of the development in IoT. This system creates replicas or mirror images of the devices that is more easily accessible through the URL. As large volumes of data are being created, the metadata can help in the transfer of this data. IPV6 is also a good option to be able to uniquely identify things and monitor and control them. Another important task is the development of lightweight IPV6 for home appliances.
1.1.1.4 Data Storage and Analytics
The unprecedented outcome of any emerging field is the generation of a large amount of data. The storage and management of the data, ownership, and expired data issues have gained importance. According to statistics 5 percent of the totally generated energy is being used by the internet. As days go by, this statistics will change; it simply means the demand will increase. Hence the harvested energy using data centers needs to be figured out plans for conserving energy. The storage and use of data should be done smartly. It is imminent to design AI algorithms that could be implemented in a centralized or a distributed way. Fusion of algorithms needs to be designed to interpret the collected data. In the state-of-the-art various methods like nonlinear, genetic algorithms, temporal machine learning methods based on evolutionary algorithms, neural networks, and other artificial intelligence techniques are required to gain control of automated decision making. These systems have abilities like interoperability, integration, and adaptive communications. They also have modular architecture in hardware as well as in software parts, which is required for any IoT application.
1.1.1.5 Cloud Processing
The data is useless if there is no provision to store, collect, or analyze that data. This is made possible with the help of Cloud computing. The collected data needs to be analyzed to deduce if any action is necessary, depending on the results. For example, when a person is reaching home from work, then the thermostat can be turned on depending on the distance between his current location and home, so that when that person reaches home the temperature will be perfect. On reaching the front gate, the gates will be opened and the person can drive in. This is made possible because things collaborate and take actions if necessary, which is made possible due to Cloud processing. The thermostat and the front gate have sensors which sense the current situation and act on it with the help of Cloud.
1.1.1.6 Security
Security is very important in any domain. In IoT the sensors, their connecting interfaces, communication among them, infrastructure for the system, Cloud processing, and storage require security at every step. When IoT products were being developed, security was not the biggest concern at the time. Because of this flaw many companies still haven’t implemented the IoT measures. As time progressed, it became evident that security in the system needs to be strengthened. As hackers are tampering with vehicle control systems, for example, more stringent security measures are needed to be implemented. Hence many companies are asking for IoT products that have strong security systems that will be difficult to breach.
1.1.1.7 Visualization
Visualization is a very important milestone in the creation of an IoT application. This visualization helps users to easily communicate with the environment. The displays (phones, tablets) nowadays are designed to be more intuitive so that users will be able to reap full benefit from it. For a layman, it is very important to get the information needed in a more precise, compact, and easily understandable format. That is why visualization is very critical. As displays are evolving from 2D to 3D versions, more information can be made available to the user. This will in turn help policymakers to transform data into meaningful knowledge. This consists of visualization and detection of the associated raw data.
