Exploring IoT and Cloud Computing

Role of Cloud Computing in the Internet of Things (IoT)

Cloud computing and IoT complement each other. Cloud computing allows IoT devices to record, capture, process, analyze, and store data at a massive scale. 

Together, IoT and cloud computing services streamline cost-effective automation and data analytics. 

When we look at the ways IoT helps modern business, user analytics is one of the major drivers for IoT adoption. Businesses use the cloud and IoT to analyze big data to reveal patterns, trends, and associations.

Relationship between IoT, Big Data, and Cloud Computing

Modern IoT solutions are built on a basic premise — helping businesses optimize operations. Cloud computing helps process all the data generated by the IoT. Big data analytics plays a large role in making IoT solutions efficient at automation and optimization. 

Cloud computing takes care of storage and security for an IoT-based app. At the same time, cloud computing acts as a bridge between the IoT platform and big data. 

Cloud computing services enable IoT solutions to act intelligently by handling:   

Data storage and communication

Cloud computing paves the way for IoT devices to the internet for data storage and processing. The data can then be used by any other complementing technology, system, or solution remotely.

Think of it like this  —  you ask Alexa, a consumer IoT device to find you the nearest restaurant. Alexa connects to a cloud application like Google Maps and provides you the results. Data feed (your voice), the IoT device (Alexa), and the cloud application (Google Maps) interact to give you the right result here. 

Data security

Saving large data volumes generated from IoT devices can be a security nightmare. Cloud allows encrypting critical operational data while bringing down the costs of storage. 

Your business doesn’t have to invest in server infrastructure and security. Plus, you get high-end security measures embedded in the cloud. Using the cloud for IoT helps in reducing the chances of leaks and cyber attacks.

IoT Cloud Computing for Mobile Apps 

Big data, cloud, and IoT work hand-in-hand in many use cases across industries. Data feeds from connected devices can be substantial. The cloud allows mobile apps to handle vast volumes. On top of that, the cloud is scalable as per business needs.

The cloud IoT simplifies the process of communication and transfer of data between IoT devices. Also, the cloud serves as a hosting platform for high-end data analytics when it comes to IoT apps. 

A mobile app can use the cloud-IoT synergy for deriving large-scale actionable insights, quickly and at scale.

BEAT81 uses IoT, cloud, and big data to help people stay fit and healthy. The app uses heart rate monitor, fitness data, and statistics to find the best fitness programs online or near users. Here, cloud computing helps the app provide smart suggestions based on fitness levels and progress.

Why Does Your Mobile App Need IoT Cloud?

Data is now more valuable than anything else for any startup or company. Data helps artificial intelligence (AI) solutions become smarter and more user-friendly. 

With mobile apps becoming more AI-driven, the cloud offers immense benefits for app startups. Cloud makes it possible to collect, store, and process user data to offer contextual recommendations powered by AI.

Here’s how cloud IoT can improve your mobile apps:

Unlimited scalability potential

Cloud-based solutions are easier to scale compared to legacy systems. For a mobile app, keeping up with increasing user data every day can get hard. You’d need more infrastructure: servers and hardware whenever you cross your thresholds.  

When user data is handled by a cloud-based solution, it just takes less time to set up a virtual server or add more cloud space. Your solution can scale quickly, vertically or horizontally based on data usage. 

Scalability on the cloud means the big data processing possibilities are endless. You can enjoy faster analytics without hassle or added costs. Modern cloud services like Amazon AWS provide amazing scalability based on usage and storage limits.

Responsiveness and easy access 

Data stored on the cloud can be remotely accessed from anywhere in the world. This facilitates real-time data analysis and faster response times. 

When it comes to smart responses and intelligent recommendations, fast is always better. The cloud speeds up analytical capabilities, making connected apps faster at decision making. Apps become more tactile, responsive, and reliable thanks to cloud integration.

Also, connected IoT devices can be effectively tracked round the clock. You can update sensor firmware and process captured data in real-time without being present at a particular location. 

Shorter time-to-market (TTM)

Oracle reveals that using cloud-based architecture can speed up app development by up to 50%. 

In a world of MVPs, time is a valuable commodity. Cloud IoT is faster to deploy and manage than an on-premise solution.

While on-premise systems can be customized, it takes a lot of time for development and deployment. When you deploy a cloud-based solution, you needn’t worry about building analytical capabilities. 

Cloud computing can handle data capturing and storage to security and analysis out-of-the-box. If you need to deploy a solution quickly without compromising on reliability, the IoT cloud is a great way to make it happen. 

Improved security 

Maintaining a secure IoT ecosystem can be really hard for app-based startups. 40% of cybersecurity professionals agree that the public cloud is more secure than on-premise solutions.

AppSec measures also became simpler to implement on the cloud. Cloud security posture management (CPSM) solutions can automate the discovery of vulnerabilities.

Zscaler CSPM is a powerful CPSM tool that protects data by managing misconfigurations to reduce security risks. 

Cost-effectiveness 

Cloud reduces upfront investment when it comes to building and deploying a large-scale IoT solution. Also, the cost of data processing is reduced thanks to the flexible structures of modern clouds.

Managing an on-premise server to support a large volume of data is a lot of work. It requires a dedicated team. Even though, when there’s an on-site emergency and the infrastructure fails, the entire system can suffer significant downtime. 

When it comes to IoT apps, using the cloud is the logical and cost-efficient strategy for early-stage startups.

Frequently Asked Questions

Is cloud computing necessary for big data?

No. It isn’t necessary but definitely preferable. Big data processing involves analyzing large data sets to derive valuable insights. Cloud computing services give apps and IoT solutions the power to make it happen at scale without massive investments.

What are IoT cloud platforms?

IoT cloud platforms are developed by utilizing multiple progressive technologies — cloud, IoT, big data, AI, etc. IoT clouds allow businesses to operate and scale their operations with extreme efficiency. It facilitates data transfer, communication, automation, and several other applications essential for growing businesses in the 21st century.

How is the cloud used in IoT?

Public or hybrid cloud systems are the backbone of IoT solutions. They help in data storage, processing, security, and analysis. Using the cloud to capture data from thousands of connected devices creates a streamlined system that’s capable of handling large volumes for real-time data analysis.

Does net neutrality influence cloud computing and IoT services?

Net neutrality ensures equal treatment of all internet data, crucial for cloud computing and IoT services. It prevents ISPs from blocking, throttling, or prioritizing certain data, which could hinder IoT device performance and cloud service accessibility.

Is cloud computing necessary for IoT?

For a modern IoT infrastructure, the cloud is extremely crucial. As the business world becomes more dependent on connected tech, the cloud helps manage large volumes of data. This helps businesses to run IoT-powered operations at scale with no investment towards building on-premise architecture for data analytics.