The Internet of Things (IoT) is the network of physical devices, vehicles, and any other items embedded with electronics, software, sensors, actuators, and connectivity which enables these objects to connect and exchange data.

The internet of Things envisions a world where both ordinary and exotic devices are connected wirelessly to the Internet and to each other. This will mean that devices that do not already have a network connection may have one added in the future to enable it to communicate with the IoT ecosystem seamlessly.

One of the most basic use cases of IoT is to connect devices to the internet so that they can report their status. For example, an IoT device could be a temperature gauge, a location sensor, device measuring humidity or a circuit that measures vibration. These sensors then can be attached to manufacturing machinery so that the data transmitted could help business teams to track the machine’s operations. The data gathered could be used for tracking maintenance, improving production efficiencies, reduce downtimes, increase safety and much more.
Most IoT projects are motivated by a need to reduce operating costs or increase revenue.

The depth and breadth of IoT applications are creating new opportunities, providing new markets for existing business and improving operations efficiencies. Machina’s Research predicts the value of the IoT market to rise to $ 4 trillion USD by 2025.

Internet of Things – Lifecycle:

Stages in the IoT lifecycles are below:

1. Collection of Data – The data is collected through devices and sensors. Sensors detect and measure information on all sorts of things like temperature, humidity, pressure, etc. And this collected data is communicated in some form, such as a numerical value or electrical signal.  Typically, the data is collected at home, inside a car, manufacturing plant, warehouse, etc.
Some of the examples of sensors are Temperature sensors, Proximity Sensors, Accelerometers, IR Sensors, Pressure Sensors, Light Sensors, Ultrasonic Sensors, Smoke/Gas sensors, etc.

2. Communication – Sending the collected data and events through the network to some destination. The data is sent to Cloud platforms, Private Data centers, Home networks, etc. through the communication network. Various options for communication are:

1.  Cellular network – Low range, High bandwidth.
2. WiFi – Very low range, very high bandwidth.
3. 6LowPAN, LoRa WAN, Sigfox, Zigbee – High range, low power, low bandwidth.
4. Bluetooth – Low range, low power, low bandwidth.
5. NB-IoT.

3. Analysis – Creating information from the data. Data Analytics tools help you make sense of the received data. Using the Data Analytics tools, one can:

1. Convert, combine and calculate new data.
2. Schedule calculations to run at certain time.
3. Visually understand relationships in data using built-in plotting functions.
4. Combine data from multiple channels to build a more sophisticated analysis.

4. Action – Taking the required action based on the information & data. This could just be an intimation upon a particular event or threshold being reached to set up a more intricate action such as turning on/off a machine upon a particular threshold. You can also remotely control devices using the complete IoT infrastructure.
Communicate with other machines (M2M), Send notification, talk to another system, etc.

Components of IoT:

1. Smart Devices & Sensors – Devices and sensors are the components of the device connectivity layer. These smart sensors are continuously collecting data from the environment and transmitting the information to the next layer.
Sensors are often integrated circuits that are designed for these kinds of IoT/M2M applications. Small size and low cost of these chips makes it an appropriate choice. For example, many of the sensors are even available in high-end smartphones.
In most of these typical sensors, the specific mechanism used to measure the physical parameter depends on the ranges being measured, the sensitivity and accuracy desired, whether the sensor could be exposed to adverse environmental conditions, the cost target, etc.

2. IoT Gateway – IoT Gateway manages the bidirectional data traffic between different networks and protocols. Another function of the gateway is to translate different network protocols and make sure the interoperability of the connected devices and sensors.
This device may be a unit serving a single sensor and associated application. More often, a gateway is a product with multiple short-range wireless and wired connections to local sensors and long-range wireless or wired connection to the remote servers. Gateways can be configured to perform pre-processing of the collected data from thousands of sensors locally before transmitting it to the next stage.
IoT gateway offers a certain level of security for the network and transmitted data with higher-order encryption techniques. It acts as a middle layer between devices and cloud to protect the system from malicious attacks and unauthorized access.

Cloud Server & Analytics

1. Cloud/Application Servers – Internet of things creates massive data from devices, applications, and users which has to be managed in an efficient way. IoT cloud offers tools to collect, process, manage and store huge amounts of data in real-time. Industries and services can easily access these data remotely and make critical decisions when necessary.
Basically, IoT cloud is a sophisticated high-performance network of servers optimized to perform high-speed data processing of billions of devices, traffic management and deliver accurate analytics. Distributed database management systems are one of the most important components of IoT cloud.
Cloud system integrates billions of devices, sensors, gateways, protocols, data storage and provides predictive analytics. Companies use these analytics data for improvement of products and services, preventive measures for certain steps and build their new business model accurately.

2. Data Analytics – M2M and IoT devices usually report data in constant streams, and these must be processed in real-time or near-real-time. This is a shift from traditional programming frameworks that open a file, read it, process the contents, and then close it. Today, real-time analytics is possible on streaming IoT/M2M data.
Another key to IoT/M2M analytics processing has been the development of open-source distributed storage and distributed processing frameworks. This allows the processing of very large data sets over computer clusters.
With these scalable technologies capable of managing streams of Big Data, businesses can use various types of analytics to better understand and use the data their IoT/M2M sensors collect. Analytics can help organizations in their decision-making processes thru:

• Descriptive Analysis (What Happened?)
• Diagnostic Analysis (Why did it happen?)
• Predictive Analysis (What may happen?)
• Prescriptive Analysis (How to reduce risks?)

3. User Interface – User interfaces are the visible, tangible part of the IoT system which can be accessed by users. A well-designed user interface ensures minimum effort for users in obtaining the right information and also encourages more interactions.
Modern technology offers many interactive designs to ease complex tasks into simple touch panels controls.