The Internet of Things, or IoT, is a network of physical devices. These devices can transfer data to one another without human intervention. IoT devices are not limited to computers or machinery. The Internet of Things can include anything with a sensor that is assigned a unique identifier (UID). The primary goal of the IoT is to create self-reporting devices that can communicate with each other (and users) in real time.
Who coined the term Internet of Things?
The IoT was named by computer scientist Kevin Ashton in 1999.
Probably the most familiar form of connectivity for the internet, and for IoT, is Ethernet. In addition to Ethernet, IoT devices can connect using a wide variety of other technologies. The connectivity objective is that an IoT platform support as many modes of connection — wired and wireless — as possible. Wireless options include ANT+, Bluetooth, EDGE, GPRS, IrDA, LTE, NFC, RFID, Weightless, WLAN, ZigBee, and Z-Wave.
IoT software applications are emerging for businesses in virtually every industry as well as for home users. These applications provide much of the automation capabilities that make IoT solutions so valuable. These software and middleware applications help businesses drive down costs, increase efficiency, and improve regulatory compliance. To achieve these goals, an IoT platform should be compatible with applications specific to your industry.
The number of devices connected to IoT will soon reach anywhere from 28 billion to 50 billion, depending on who you ask. IoT sensors gather information about conditions in their vicinity, such as temperature or moisture level. IoT actuators perform specific tasks, such as turning things on or off, and recording information about its triggers and subsequent reactions. In addition, IoT wearables of various kinds, like a health-tracking bracelet, can record your health statistics and other data such as your location. In essence, the functional requirement for an IoT platform is that it has the ability to manage a heterogeneous set of devices.
Devices that we discussed above don’t just perform tasks. In most cases, they will also report on the tasks they perform. Through their connection to an IoT platform and to each other, they will transmit detailed data about their actions. Typically, there will be no need for human intervention in the process. The devices will simply send data, potentially in real-time, for storage and analysis. To give you an idea of just how much data is involved, one estimate foresees the IoT generating around 400 ZB (zettabytes) by 2018. Functionally, therefore, an IoT platform must be able to support storing massive amounts of data.
The vast volumes of data discussed above have the potential to provide unprecedented insights into consumer behavior and preferences. Unlocking those insights, however, requires powerful analytics tools. A key IoT platform functionality, therefore, is that it is capable of either incorporating — or offering compatibility with — analytics solutions that will translate significant amounts data into useful and actionable insights.
The Internet of Things (IoT), is a technology that links gadgets to the internet so they may share and exchange data. The device is the first pillar of IoT. Your smartphone, hospital medical equipment, a vehicle, or any other electronic item that can transport data over the internet can be this device. These gadgets have sensors that capture and send data from one location to another. IoT devices need wireless networks that enable several devices to function on a same network in order to stay connected. For IoT devices to operate without interruption, a wireless solution is necessary. Mobile devices, medical equipment, cars, and electronic appliances are all examples of IoT devices.
The prior aim of IoT is to collect & store data. This data is processed to enhance the functionality of various devices and software. Data plays a crucial role in the system. One example of this is exercise applications that monitor user movement to generate relevant data for tracking fitness goals. The primary function of IoT is to gather a large amount of data to improve application functionality and process information. For instance, music streaming services collect data on the music and artists that users listen to, and exercise applications use location trackers to track users’ movements and physical activities. Enterprises typically integrate IoT with their HVAC and security systems to control them centrally or remotely. Different forms of data can be collected, but status data is the most common and simplest form. This data is then used for complex analysis.
The proper analysis and efficient processing of data are crucial for the effectiveness of IoT applications in daily life. The use of data analysis tools and procedures is employed to analyze the various types of generated data. This analysis helps in obtaining valuable information, which can then be used to optimize and enhance the benefits of IoT for the user. The third pillar of IoT is analytics, which is responsible for the efficient and accurate analysis of collected data. Analytics is what makes any device powerful and valuable in an individual's life by enabling the proper functioning of the transmitted data. Analytics, for example, let you keep track of your daily steps walked and the equivalent number of calories burned in a workout app.
The fourth and final pillar of IoT is connectivity, it allows the previous three pillars to coexist peacefully. It is crucial to maintain uninterrupted connectivity to ensure the smooth flow of real-time data processing and analysis. Without connectivity, it is impossible to optimize the processing and use of data in different systems and software. Poor connectivity can also cause inaccuracies and data loss during data analysis. Connectivity is essential for the three previously mentioned pillars to work in conjunction with each other. Therefore, to ensure a consistent flow of data from the device high-bandwidth communication with few interruptions is needed. Without this regular flow of data, no data analysis could take place & the optimization of systems would not be possible. Any data that was collected might also be inaccurate due to the loss of potentially valuable data caused by poor connectivity.
Remote monitoring of equipment performance metrics and early detection of potential malfunctioning. Prevents equipment breakage and production interruptions.
Used in: Manufacturing.
Automating manual actions based on commands sent from control apps to actuators. Applicable to simple actions like switching on/off, opening/closing, and complicated industrial processes, like robotic order picking.
Used in: Manufacturing, Smart home.
Measuring the required environmental metrics (temperature, humidity, pollution, CO2 level, etc.). Helps check the compliance of asset storage and transportation, monitor operation conditions for industrial equipment and at human workplaces, understand the environmental impact of processes.
Used in: Smart city, Production floors, Agriculture.
Automated control over the intensity of energy utilization depending on the outside conditions. Applicable to personal (home lights) and public (street lights) surroundings.
Used in: Smart home, Smart city.
Remote tracking of assets’ geoposition and movements. Instant indication of low stock.
Used in: Storage facilities.
Analyzing vital signs measured by wearable devices and informing a supervising doctor on deviations from normal levels. An advanced level of telehealth.
Used in: Healthcare.
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