Internet of Things, Big Data and Cloud – What do these concepts have in common?

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Written by: Marketing Team

These days, with every company looking for ways to gain a competitive advantage, more and more of them are starting to see the enormous potential of the Internet of Things. Why? It is because this technology allows you to generate huge amounts of data, which, combined with Big Data and cloud computing, can develop processes, increase operational efficiency and significantly improve customer experience.

Sounds interesting? In this article, we will explain what the Internet of Things, Big Data and Cloud are and what these three important business concepts have in common. What’s more, we will present proven ways to store and analyse data from IoT devices.

What is the Internet of Things?

Internet of Things (IoT) refers to devices (things) that are connected to the Internet and other types of equipment that collect, process and share a range of data about the environment.

At every step, we are accompanied by intelligent devices, which became an integral part of our everyday life. These include various types of items, such as smart refrigerators, cars and systems that remember the user’s behaviour and can adapt to it over time.

What is Cloud Computing?

Cloud, or, more broadly, Cloud Computing is an IT term defining services which:

  •     are available via the Internet,
  •     are scalable,
  •     cost less or more, depending on our usage (pay-as-you-go).

What are the types of cloud services? Cloud Computing services can be divided into three main categories:

  1. Infrastructure as a Service (IaaS),
  2. Platform as a Service (PaaS),
  3. Software as Service (SaaS).

The cloud is available in three services:

  • private –  one that can be accessed by all Internet users. Examples of public clouds include GCP, AWS, Azure;
  • public – an infrastructure built by companies for their internal needs, often in their own DataCenter;
  • hybrid – a combination of private and public clouds. It means that some services are built internally, even though the company uses the public cloud as well.

For the purposes of this article, let’s assume that whenever we talk about Cloud, we mean the public cloud.

Big Data – What is it?

Big Data, as the name suggests, is a data collection of enormous size in terms of volume, capacity and complexity. It is difficult to process it in local data centres (small, compared to data centres of the previously mentioned, gigantic public clouds). Big Data is usually stored by the organisations and companies that constantly generate new information from many different sources, such as, for example, e-mails, user accounts or advertisements.

In business, Big Data technologies also refer to the process of collecting and analysing data sets, so that the companies can discover hidden patterns of their activity and gain valuable insights and draw conclusions.

In the case of the Internet of Things, such information may include user preferences and smart devices usage details. For example, an intelligent heating system collects information about the temperature preferred by household members in a given room at a specific time. Thanks to this knowledge and data such as weather information, it is able to set the right temperature, tailored to the lifestyle of the household members.

IoT, Cloud Computing and Big Data - How are they related?

All the three concepts combine and complement each other, creating many business opportunities. In short, cloud computing enables IoT to collect and store data generated by smart devices and Big Data allows it to be properly processed, analysed and presented.

Imagine this: You ask a smart speaker such as a Google Home Speaker (IoT device) what the weather will be tomorrow. The speaker connects to a weather app in the cloud and gives you the information. The data (your message), the IoT device (smart speaker) and the cloud application connect to get a specific result, which is giving the correct information to the user – you.

Large amounts of data require high and reliable computing power to be processed in real time. Thanks to public computing clouds with almost unlimited resources, we can use the enormous potential of Big Data technologies.

How do modern companies store large amounts of data from IoT devices?

There are at least several ways to store and process data (not only generated by IoT): 

  • On premise – a model in which data is stored locally, e.g. in a company’s server rooms.
  • Cloud platforms – a solution where a company uses the cloud services of an external provider (e.g. Google Cloud Platform).
  • Collocation services – a model in which a company rents a server room with the service provider’s servers. To simplify, let’s put all the mixed computing resource delivery models in this category.

Today, an increasing number of companies opt for the cloud. The cost of creating and maintaining an infrastructure is high and achieving a security level similar to that of the largest data centres often exceeds the company’s ability. Currently, cloud platforms ensure the highest standards of data security, which minimises the risk of possible data leaks or cyberattacks. In addition, they are available immediately and enable easy scaling, according to the company’s needs.

Popular cloud platforms for storing data from IoT

Currently, there are many cloud platform providers on the market. So how to choose the best one? We are a long-term partner of the key providers. Based on our experience, we can confidently recommend three proven solutions.

1. Google IoT Cloud Platform

At Solwit, we use Google Cloud Platform, so that our clients have a set of tools for processing data generated by their IoT devices. This solution focuses on improving business processes in companies where it is crucial to have a quick insight into valuable conclusions and monitor market trends. Google cloud computing provides fully scalable integration that enables connecting, storing and analysing data in real time.

An example combination is a set of the following services:

  • BigQuery – Data Warehouse as a service intended for analytics of huge amounts of data (possibly in real time);
  • Vertex AI – a platform that offers all Google services related to Machine Learning;
  • Google Data Studio – a tool for data visualisation.

2. Amazon Web Services IoT Platform

Amazon is the first cloud computing provider that turned this service into a product back in 2004. Their platform is very scalable and, according to Amazon, can support up to billions of devices. 

Currently, they offer a very comprehensive set of tools, which enable, among others, secure messaging, full integration with data analysis services, integration with ML (Machine Learning) services and IoT devices management.

Amazon cloud computing, like other public cloud providers, offers a software development kit (SDK), allowing easier integration with AWS and faster development of applications based on their services.

3. Microsoft Azure IoT Hub

Microsoft is another big player on the market of cloud platforms for IoT. It offers many important functionalities on their Azure cloud computingcloud platforms. Among them, there are solutions linked with machine learning and data analysis.

Other cloud platforms include: IBM Watson IoT Cloud Platform, Oracle IoT, Salesforce IoT, Bosch and Cisco IoT Cloud Connect.

Why is it worth analysing IoT data?

The ability to receive real time data can be a breakthrough, especially for companies whose performance depends on the equipment’s proper functioning. IoT data analytics allows companies to plan the best time for possible downtime and to quickly receive information about any errors. 

At this point, it is worth mentioning the increasingly popular predictive maintenance, a method which consists in collecting a lot of important data, e.g. about the condition of machines, the number of manufactured elements or the environment (including temperature, humidity, pressure, dustiness) in real time. Its comprehensive analysis, often with the use of Machine Learning methods, can provide a well-functioning model for predictive maintenance. Thanks to this practice, companies can predict when to carry out maintenance on certain equipment, preventing possible interruptions in production.

IoT data analytics can also be used to generate valuable tips and improve customer experience, which translates into a sales growth. By collecting data about the needs and preferences of customers, companies can offer them what they are actually looking for and make better business decisions based on data and not on assumptions.

How to analyse IoT data?

The process of implementing data analytics tools and systems should be tailored to the needs and specificity of a particular company. There are three basic elements to consider:

  1. Data collection – where and how it is collected.
  2. Data validation – verifying its correctness.
  3. Data analysis – what it is for.

The most popular tools related to IoT data analytics are:

  • Google Cloud IoT Core – software that allows devices to connect to the cloud in a safe way and process messages. It features easy device registration and quick implementation of IoT. This solution enables the collection of multiple data streams, which makes data management easier. 
  • ThingSpeak – an open-source solution that allows you to quickly build IoT prototypes and analyse or visualise data using MATLAB widgets. 
  • AWS IoT Analytics – a platform that allows you to perform complex analyses on huge amounts of IoT data.

Frequently Asked Questions

We are aware that this subject may raise many questions and we will address the most popular ones below. However, if there is an issue that we have not mentioned, please contact us. We will be happy to answer any questions that raise your doubts.

1. What are the benefits of the IoT cloud model?

Most importantly, cloud-based IoT solutions are flexible. Environments scale (both up and down), depending on the number of devices or the traffic they generate. Moreover, the IoT data processing system can be easily extended with other components, e.g. data analytics or visualisation. In addition, it is worth remembering that cloud services for IoT also ensure the highest security of both data transmission and storage.

2. What is IoT Proof of Concept (PoC)?

PoC is a mini-project that will answer the question whether a given technology is suitable / meets the requirements necessary to build the target production solution. Our team works with you to achieve the final effect of a product: we create the main architecture of the solution and specify business, technical and test requirements. We create a project plan with specified milestones and batch documentation for individual areas along with metrics which will be tracked within the project. Confirmation of the initial assumptions at the beginning of cooperation guarantees the product you expect.

3. What is “on premise”?

On-premise means that a given resource (in this case a computer system) is owned by a given company – in production, in an office or in a server room.

4. How much data can I upload to the cloud? Are there any restrictions? If so, what are they?

There are practically no restrictions. Big Data in the cloud reaches the level of petabytes. It is really just a matter of the costs we pay for the resources we use.

5. Can data in the cloud crash?

There is always a risk of failure and data loss, but in the cloud technologies the level of this risk is very low. The availability of cloud services is often set at 99.99%. An interesting fact is that reliability (durability) for Google Cloud Storage amounts to 99.999999999%.

6. What is the best protocol for transferring data from IoT to the cloud?

The most popular protocols for IoT support are MQTT (Message Queuing Telemetry Transport) and HTTP (Hypertext Transfer Protocol). You can also encounter the AMQP (Advanced Message Queuing Protocol), COAP (Constrained Application Protocol) and DDS (Data Distribution Service) protocols. The MQTT protocol owes its growing popularity to its speed and small demand for resources, as well as generating less network traffic, compared to the http protocol.

The table below shows the protocols supported by the most popular platforms:

 Platform Protocols
1Microsoft AzureMQTT, AMQP, HTTPS, MQTT over WebSockets, AMQP over WebSockets
2AWSMQTT, HTTPS, Websockets, LoRaWAN 
3IBM BluemixMQTT, HTTP, HTTPS
4ThingworxMQTT, HTTPS, HTTP, COAP
5GoogleMQTT, HTTP

7. Does data have to be sent to the cloud continuously?

Data can flow into the cloud in an irregular stream as sometimes IoT devices do not have a permanent connection to the network. Cloud services are (nearly) always ready to go.

8. Can I transfer data such as updates and control information from the cloud to IoT?

Definitely yes. The connection to cloud services can be bidirectional.

9. What is the average monthly cost of the cloud for an average IoT device?

It depends on the provider you choose and the billing model it offers. The total cost depends on many factors, such as the amount of processed data or the use of other services in the system.

Use the potential of IoT, cloud computing and Big Data in your business

Do you want to implement IoT solutions in your company? Or, perhaps, you need a partner who will help you find the best solution for collecting and analysing data? If you are wondering which option to choose, we will be happy to advise you. 

 
Moreover, if you choose the cloud, we can implement PoC for you. At Solwit, we will build the appropriate architecture for you, transfer your data to the cloud and configure transparent reports. Contact us and get a free consultation!

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