IoT Enabling Technologies

IoT is enabled by several technologies including wireless sensor networks, cloud computing, Big data analytics, Embedded Systems, Security Protocols and architectures, communication protocols, web services, Mobile Internet, and Semantic Search engines.

So toady i provides an overview of some of these technologies which play a key-role in IoT.

IoT Enabling Technologies

Wireless Sensor Networks

A wireless sensor network comprises of distributed device with sensor which are used to monitor the environmental and physical conditions. A WSN consists of a number of end-nodes and routers and a coordinator. End Nodes have several sensors attached to them in node can also act as routers. Routers are responsible for routing the data packets from end-nodes  to the coordinator. The coordinator collects the data from all the nodes.  Coordinator also act as a gateway that connects the WSN to the internet. Some examples of WSNs used in IoT systems are described as follows:

  • Weather monitoring system use WSNs in which the nodes collect temperature humidity and other data which is aggregated and analyzed.
  • Indoor air quality monitoring systems use WSNs to collect data on the indoor air quality and concentration of various gases
  • Soil moisture monitoring system use WSNs to monitor soil moisture at various locations.
  • Surveillance system use WSNs for collecting Surveillance data (such as motion detection data)
  • Smart grid use WSNs for monitoring the grid at various points.
  • Structural health monitoring system use WSNs to monitor the health of structures ( buildings, bridges) by collecting vibration data from sensor nodes de deployed at various points in the structure.

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Cloud Computing

Cloud computing is a trans-formative computing paradigm that involves delivering applications and services over the Internet Cloud computing involves provisioning of computing, networking and storage resources on demand and providing these resources as metered services to the users, in a “pay as you go” model.  C loud computing resources can be provisioned on demand by the users, without requiring interacyions with the cloud service Provider. The process of provisioning resources is automated. Cloud computing resources can be accessed over The network using standard access mechanisms that provide platform independent access through the use of heterogeneous client platforms such as the workstations, laptops, tablets and smartphones.

cloud computing
cloud computing

Cloud computing services are offered to users in different forms:

Infrastructure as a Service (IaaS): hardware is provided by an external provider and managed for you

Platform as a Service (PaaS): in addition to hardware, your operating system layer is managed for you

Software as a Service (SaaS): further to the above, an application layer is provided and managed for you – you won’t see or have to worry about the first two layers.

Big Data Analytics

Big Data analytics is the process of collecting, organizing and analyzing large sets of data (called Big Data) to discover patterns and other useful information. Big Data analytics can help organizations to better understand the information contained within the data and will also help identify the data that is most important to the business and future business decisions. Analysts working with Big Data typically want the knowledge that comes from analyzing the data.

Some examples of big data generated by IoT systems are described as follows:

  • Sensor data generated by IoT system such as weather monitoring stations.
  • Machine sensor data collected from sensors embedded in industrial and energy systems for monitoring their health and detecting Failures.
  • Health and fitness data generated by IoT devices such as wearable fitness bands
  • Data generated by ioT systems for location and tracking of vehicles
  • Data generated by retail inventory monitoring systems

Characteristics

Big data can be described by the following characteristics:

  • Volume – The quantity of generated and stored data. The size of the data determines the value and potential insight, and whether it can be considered big data or not.
  • Variety – The type and nature of the data. This helps people who analyze it to effectively use the resulting insight. Big data draws from text, images, audio, video; plus it completes missing pieces through data fusion.
  • Velocity – In this context, the speed at which the data is generated and processed to meet the demands and challenges that lie in the path of growth and development. Big data is often available in real-time. Compared to small data, big data are produced more continually. Two kinds of velocity related to Big Data are the frequency of generation and the frequency of handling, recording, and publishing.
  • Veracity – It is the extended definition for big data, which refers to the data quality and the data value. The data quality of captured data can vary greatly, affecting the accurate analysis.

Communication protocols

Communication protocols form the backbone of IoT systems and enable network connectivity and coupling to applications. Communication protocols allow devices to exchange data over the network. Multiple protocols often describe different aspects of a single communication. A group of protocols designed to work together are known as a protocol suite; when implemented in software they are a protocol stack.

Internet communication protocols are published by the Internet Engineering Task Force (IETF). The IEEE handles wired and wireless networking, and the International Organization for Standardization (ISO) handles other types. The ITU-T handles telecommunication protocols and formats for the public switched telephone network (PSTN). As the PSTN and Internet converge, the standards are also being driven towards convergence.

In IoT we used MQTT, COAP, AMQP etc. protocols. You can read in detail by given below links.

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Embedded Systems

As its name suggests, Embedded means something that is attached to another thing. An embedded system can be thought of as a computer hardware system having software embedded in it. An embedded system can be an independent system or it can be a part of a large system. An embedded system is a controller programmed and controlled by a real-time operating system (RTOS) with a dedicated function within a larger mechanical or electrical system, often with real-time computing constraints. It is embedded as part of a complete device often including hardware and mechanical parts. Embedded systems control many devices in common use today. Ninety-eight percent of all microprocessors are manufactured to serve as embedded system component.

An embedded system has three components −

  • It has hardware.
  • It has application software.
  • It has Real Time Operating system (RTOS) that supervises the application software and provide mechanism to let the processor run a process as per scheduling by following a plan to control the latencies. RTOS defines the way the system works. It sets the rules during the execution of application program. A small scale embedded system may not have RTOS.

So these are some IoT Enabling Technologies.

Harshvardhan Mishra

i am an IoT Enthusiast and Part Time Tech Blogger.

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