What Is The Internet Of Things (IoT) And Edge Computing

 What Is The Internet 

 Of 

 Things? IoT 

In simple terms, the Internet of Things (IoT) refers to the constant tendency to connect all kinds of physical objects to the Internet, especially those that you may not even imagine. It can be any type of element, from common household objects, such as refrigerators and light bulbs; business resources, such as shipping labels and medical devices; to unprecedented wearables, smart devices, and even smart cities that only exist thanks to the IoT.

To be more specific, the term IoT refers to systems of physical devices that receive and transfer data over wireless networks without human intervention. What makes this possible is the integration of simple computing devices with sensors in all kinds of objects. For example, a "smart thermostat" ("smart" usually means "IoT") receives data from the location of your smart car while you are driving, and uses it to adjust the temperature in your home before it arrives. This is accomplished without your intervention and produces the result that is better than if you had to manually adjust the temperature before leaving or upon returning.

A traditional Internet of Things system, such as the smart home described above, works by constantly sending, receiving, and analyzing data in a feedback loop. Depending on the type of IoT system, people or artificial intelligence and machine learning (AI / ML) can carry out the analysis almost immediately or within a certain time. Think again about the smart home example. To predict the optimal time to control the thermostat before you get home, your IoT system can connect to the Google Maps API to get information on real-time traffic patterns in your area, and you can use the data about your driving habits that the car collects in the long term. Additionally, utilities can analyze the IoT data they collect from smart thermostat customers in order to optimize the system on a larger scale.

Consumers pay attention to the technological advancement that the IoT brings when discussing the confidentiality and security risks inherent in technologies such as portable smartwatches. If you plan to adopt an IoT project in your company, it is important to understand the consumer's perspective, especially if the end user is the general public. But surely you also want to know about the IoT from an enterprise use case perspective.

Internet Of Things - Business

From an enterprise IT perspective, IoT solutions enable companies to enhance their current systems and design entirely new endpoints for customers and partners. However, they also create new challenges for IT. The volume of data that a smart device system is capable of producing is impressive; hence the name "big data". But integrating big data into current systems and configuring analytics to act on it can be tricky. Additionally, IoT security is a critical aspect to consider when deciding how open an IoT platform should be. Still, for many companies the IoT has proven to be worth the effort. Successful business use cases can be found in almost every industry.

 ExamPles Of Business IoT 

Industrial Internet of Things (IoT) - Imagine the life cycle of heavy machinery used on construction sites. Over time, people who operate equipment put different levels of stress on them, so breakdowns are to be expected for a variety of reasons during operations. Now consider implementing specialized sensors on the parts of your machinery that are most prone to breakage and overuse. The sensors are not only used to perform predictive maintenance and improve people performance (example of real-time data collection and analysis), but also to transfer the data to the factory, for engineers to improve their designs. new models (example of long-term data analysis).

                                                                                                                                        

The Internet Of Things In Agriculture

 The IoT has revolutionized agriculture in a number of ways, including through the use of humidity sensors. By installing a series of moisture sensors in the fields, farmers can now receive more accurate data and predict when to water crops. What's more, humidity sensors connect to IoT applications that control the irrigation machinery itself and automatically activate it based on sensor data, without the need for human intervention.

                                                                                    

Internet of Things in Logistics and

 Transportation

 One of the first implementations of IoT in the logistics and transportation industry involved tagging shipping containers with Radio Frequency Identification Devices (RFID). These simple tags store digital data that a reader can record via radio waves, as long as the RFID is at a certain distance from a reader. Initially, this allowed logistics companies to track the arrival of containers at certain checkpoints where RFID readers were installed, for example warehouses or port cargo terminals. However, thanks to advances in IoT, smart battery-powered tracking devices have been developed to replace RFID. These devices can seamlessly transfer data to IoT applications without the need for on-site readers, so companies can analyze shipment data in real time at every leg of the supply chain.

                                                                                                                                

 IoT And Edge Computing 

What characteristicss must a smartphone need to be Smart?

The obvious answer is that they include a computer processor and associated hardware system that allow the phone to present a graphical interface, run an operating system, connect to the Internet, and run applications, among other tasks. In the smart home thermostat example above, the answer is similar. The thermostat is "smart" because it includes a computer system that can receive and transfer data without human intervention.

In the IoT realm, the ability of devices to use computing power is becoming increasingly valuable as a means of quickly analyzing data in real time, and for good reason. Simply sending or receiving data can be an important step in an IoT solution, but sending, receiving, and analyzing data in conjunction with IoT applications creates many possibilities.

Consider the example of RFID in the logistics and transportation industry. The first device we mentioned stores digital data that it sends to a reading device using radio waves. This reading device receives the radio waves, and then makes the information available for analysis; however, the communication between the RFID and the reader is always one-way. The RFID device itself cannot receive updates from the reader, and the reader cannot send the data or instructions back to the RFID. This limits container tracking to arrival records at certain sites, rather than constant monitoring. But what if the IoT device that tracks the containers could communicate with the IoT sensors installed in a driverless vehicle that would transport them, and everything was connected to a data analysis system managed by the company of Logistics?

To achieve this, such a logistics company would need much of the computing power available in physical IoT devices, especially for the driverless car. Instead of being simple devices that send and receive data, always waiting for instructions from a centralized data center over Wi-Fi, IoT devices would have to process the data and make decisions on their own. This deployment of computing power closer to the outer edges of a network, rather than in a centralized data center, is known as edge computing.

Computing resources and services are regularly centralized in huge data centers in a Cloud Computing Model, , accessed by end users at the "edge" of a network. This model generates economic benefits and a more efficient resource exchange capacity.  However, modern experiences for end users, such as the IoT, require computing control closer to where the physical gadget or data source really is, that's , at the "edge" of the network.

That is what edge computing is for, which is a model that distributes computing resources to the "edge" of a network when necessary, and when not, centralizes them in a cloud model. It is a solution to the problem of having to provide actionable information quickly, with data that requires immediate action. Coordinating a fleet of driverless vehicles transporting containers with smart tracking devices is an interesting example, but there are also many smaller and more practical implementations.

What Are The Main Use Cases Of Edge

 Computing?

Edge computing , can complement a hybrid computing model, especially when centralized computing is used for the following:

• Compute-intensive workloads
• Data collection and storage
• Artificial intelligence and machine learning
• Coordination operations in the different regions
• Traditional backend processing
• Edge computing can moreover offer assistance troubleshoot the data source in close real time. 

• In brief, in case decreased idleness or real-time observing can support business objectives, at that point there's a use   

case for edge computing.