IoT Techniques: The Internet of Things (IoT) is a buzzword in the domain of artificial intelligence (AI). Here is a standard explanation of IoT IoT is a technological framework where various and a large number of electronic devices are connected to the internet. It serves to transfer and analyze data through embedded sensors. It evolves fiercely as it makes the convergence of various technology stacks associated with big data and artificial intelligence.  The technological framework of IoT deals with a large number of data that is impossible to manage by a human workforce. It not only manages data well, but it also analyzes them impeccably to deliver flawless and accurate results. These aspects of IoT have made it aggressively popular in the industries of healthcare, logistics, banking, retail, and even home entertainment.  Today, over seven billion people are connected to IoT devices. Experts are highly expecting this number to grow and to touch ten billion by 2021 and 25 billion by 2025.  Now that we have a fair grasp of IoT, it is also important for us to gauge and understand its importance across various industries. 

Understanding the Importance of the IoT Techniquesfv

Affirmatively, the internet of things (IoT) has emerged to be one of the most powerful and much-demanded technologies of the 21st century. Every object (kitchen appliances, office computers, baby monitors, thermostats) that comes to your imagination can be connected to IoT. The primary purpose of connecting them to IoT is to strike seamless communications between people and things.  The IoT helps people and the digital world to be in cooperation for a smooth functioning in this hyperconnected world that will collapse without digitalization and the internet.  This is the reason why almost every industry in the world is employing IoT. Take the example of the healthcare industry that thrives on modern technology such as AI and IoT today, witnesses admissions of a large number of patients daily ever since the hit of the pandemic. This leads to overcrowding in hospitals and clinics that can increase the chances of contamination. Managing the records of patients is equally important. To overcome such problems, medical practitioners and medical professionals today rely on IoT to record and monitor their patients. Several hospitals today use IoT for crown management as well. While IoT facilitates proper handling of the logistics and conducts in a hospital eliminating chaos, the human workforce can invest themselves in more value-added activities.  We now have a fair idea about IoT and its importance across all industries. However, just knowing about IoT and its importance is not enough as IoT Techniques need to be scaled in regular intervals. Additionally, there are also challenges involved in IoT integration.  It is now time that we dive straight into the scalability techniques and challenges of IoT. 

The Five Scalability Techniques of IoT 

IoT networks and applications need to be scaled from time to time. As the number of devices and connections continue to increase at a rapid rate, the IoT framework should be made capable to tackle an increase in the number of features, the number of devices, and the number of users. The aim of scaling up IoT is to boost its performance and its longevity in handling the increase of devices and the features they bring along.  The five scalability techniques are as follows: 
  • Automated Bootstrapping 
When multiple devices are connected to IoT in the same network, it entails a host of security issues. As the number of devices continues to rise, configuring it, bootstrapping it manually can be near to impossible.  This problem can be solved with automated bootstrapping. Adding the required number of bootloaders will enable automation in IoT devices. This also increases the efficiency in handling the increasing number of devices while saving time as well. 
  • Controlling IoT Data Pipeline Better 
As already mentioned, IoT is capable of handling a huge number of data. However, the data that IoT deals with needs to be controlled by storing it in pipelines. The data generated by IoT devices need a high-throughput low-latency data pipeline that facilitates easy control of the data.  The data can be scaled up through these pipelines so that it can properly handle surges in data as well. 
  • The Three-axis Approach 
The three-axis approach consists of the x-axis, the y-axis, and the z-axis.  The x-axis scaling represents the utilization of resources and also distributing demands when received from various servers.  The y-axis scaling helps in distributing tasks that are based on the differences between the processes involved.  The z-axis helps to allocate tasks when received from different servers. 
  • Microservices Architecture
Also, known as reliable microservices architecture, applications in this type facilitate micro-process communications with each other through independent APIs.  The IoT applications are divided into small segments or functional units. To ensure smooth and proper scalability, each of these segments or functional units should be complied with before execution. 
  • Multiple Data Storage Technologies 
The multiple data storage technologies facilitate a more organized IoT scaling process because data storage is thoroughly compartmentalized.  The Challenges Entailed by IoT Scalability  Marketers and IoT stakeholders are already investing a lot in IoT as almost every industry functions with it. The rise in demand also entails certain challenges for the stakeholders. One must be ready to deal with the challenges of IoT scalability as well.  Following are the most common challenges that pop up while scaling up IoT: 
  • Network Security 
The number of devices to be connected with IoT will be on the rise. As the number increases, the risk of network security increases too.  To ensure tight network security, protocols and encrypted algorithms should be incorporated to enable high throughput. 
  • Governance
A proper governance system is required to entrust management between the users and the providers. Designing a proper governance system is one of the trending topics of AI research. 
  • Privacy
Ensuring privacy requires ensuring the concealment of IoT users. This challenge becomes hard to hold on to as the number of devices being added to the IoT network increases.  Closing Lines They say nothing is perfect. Neither is IoT. While IoT Techniques can ensure a hyper-modern world where people and machines function in harmony, it is the responsibility of the people to fix the loopholes entailed by constant evolution.  Read More: TOP INTERNET OF THINGS (IOT) TRENDS IN 2020-2021

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