Best Tools for IoT Data Processing

Many people think the Internet of things (IoT) is a futuristic phenomenon. However, it is already in use today.

IoT allows you to connect the physical world to the internet. As we speak, at least one of the following is connected to the internet: your refrigerator, manufacturing equipment, security cameras, or AC unit.

The reality is that any device that can be powered on can be a part of the IoT. It is gaining massive usage every day, and according to research firm IDC, IoT spending was $674 billion in 2017.

The IoT is expected to reach a whopping $1.1 trillion by 2021. In 2014, Cisco estimated the net worth of internet of things to be $19 trillion. Nicholas Negroponte, the co-founder of MIT Media Lab and author of being digital, said, “When we talk about the Internet of Things, it’s not just putting RFID tags on some dumb thing so we smart people know where that dumb thing is. It’s about embedding intelligence so things become smarter and do more than they were proposed to do.

The use and benefit of IoT cut across various industries, including manufacturing, supply chain, agriculture, healthcare, and energy. It is used daily by these industries to increase productivity, efficiency, and transparency.

The Internet of Things is everywhere

IoT Data Systems

One of the numerous challenges with IoT data system is the sheer volume of data that flows every minute. Parker Trewin, Senior Director of Content and Communications at Aria Systems, said, “With emerging IoT technologies collecting terabytes of personal data…” people are generating data at a high rate, in 2010, the world generated over 1ZB of data (1,000,000,000,000,000 megabytes.) That’s a lot of zeros.

The Challenges of IoT

It is important to note that every stage of IoT is filled with challenges. Chris Murphy, Editor at Information Week said “One of the myths about the Internet of Things is that companies have all the data they need, but their real challenge is making sense of it. In reality, the cost of collecting some kinds of data remains too high, the quality of the data isn’t always good enough, and it remains difficult to integrate multiple data sources.

You need to get the best out of your IoT solutions, either as a data analyst or a business owner. There are numerous challenges in every phase of the IoT process.

The first step to mitigating these problems is ensuring that the data processing system you are using is top-notch. We’ve explored a number of IoT systems. The following are our best tools for IoT data processing based on user satisfaction. To know what is required of IoT systems, it is important you understand the IoT process.

The IoT Process

The IoT Process

The IoT process starts with acquiring data from devices and sensors.

The next step is storing raw data that is sent from devices, cleaning the data by removing errors, incomplete or inaccurate records. Clean data moves to the transforming systems, where it is manipulated and transformed from one structure to the other to produce results. These results need to be stored and should be retrievable at any time.

The processes described above can be grouped into three major stages:

  1. The data is moved from sensors or devices to the cloud through suitable connectivity,
  2. Data processing,
  3. Results or output.

The result or output can be an email, image, notification, chart, or video (but not exclusively.)

Let’s explore some great IoT tools for data processing. There are numerous IoT platforms out there.

This list is not exhaustive and it is not in any order.

1. Salesforce IoT Cloud

Salesforce IoT Cloud is a cloud platform owned by It is powered by thunder. The Salesforce team says thunder is a “massively scalable real-time event processing engine.

This IoT tool is designed to handle enormous data received from devices, sensors, websites, customers, apps, and partners connected to the Cloud. It can also initiate a response in real-time.

For instance, it can automatically regulate your home if it becomes too cold or too hot, it can notify you of a break-in and send videos or pictures of the culprit.

The beauty of the Salesforce IoT Cloud is you do not have to be tech-savvy to use it. Salesforce launched its IoT Cloud in 2015 and has been soaring high ever since.

2. AWS IoT Core

AWS IoT Core is a product from Amazon Web Services. It supports HTTP, MQTT, and WebSockets, making it compatible with several industry-standard devices and sensors.

According to the AWS IoT Core team, it can support billions of devices, trillions of messages, and keep track of your connected devices. It is very compatible with other AWS services such as Amazon Machine Learning, AWS CloudTrail, Amazon Kinesis, and more. It is also known to reduce bandwidth usage.

The AWS IoT team boasts of its tight security and how it can process received data and act automatically.

Furthermore, your device doesn’t have to be online all the time. AWS IoT Core stores the last information received from your device, it stores and shows its last status and updates automatically once the device reconnects.

3. Oracle IoT

Oracle has several IoT platforms, like Asset Monitoring Cloud, it gives real-time data on asset health and usability, notify and predict asset failure.

Oracle IoT Production Monitoring is used in the manufacturing industry. It gives real-time data on your equipment, factories, production system, and products. It is particularly effective in reducing product defects.

Oracle Stream Analytics is an in-memory technology that carries out analytic manipulation on a continuous influx of massive data. It accepts data from IoT sensors, POS devices, ATMs, social media, and more. It can be accessed as a service in Oracle Cloud or installed in local systems.

Oracle Edge Analytics is used by different industries, including industrial automation, appliance management, transportation, telemetry, healthcare, smart retail vending machines, and more.

4. Particle IoT

Particle IoT pride itself as the all-in-one IoT platform. It handles a large volume of data and ensures secure communication by devices.

Its platform is user-friendly and can be used by anyone. It can be integrated with other platforms like Microsoft Azure, Google Cloud, or any IoT that supports REST API.

It integrates hardware, software, and connectivity. It processes complex data and automates responses. OptiRTC, Incorporated used a Particle platform to analyze and monitor their smart drainage system.

5. Predix

Predix calls itself the OS of the industrial internet. It is a platform for creating, deploying, and maintaining apps for industrial machinery. It securely connects machines, receives data, conducts analytics, and provides feedback. It is said to make any machine an intelligent asset.

It provides data management for predictive analytics of machines and helps avoid downtime. It is also available on mobile devices to help you monitor your industrial assets on the go. It can be used by developers, data scientists, or control engineers.

6. SQLstream

SQLstream offers easy integration for Kafka, Kinesis, and other stream users and analyses data in real time. It is easy to use, and it can analyze and trigger actions with results. It offers real-time continuous machine learning.

SQLstream offers data wrangling, data enrichment, streaming analytics, continuous egress, streaming ingestion and dashboard to visualise your data.

7. Unidots

Unidots started as an engineering service firm in 2012. It specialized in hardware and software solutions. The Unidots IoT platform offers data collection, analysis, and visualization tools. It seamlessly connects hardware, devices and sensors to the cloud.

Unidots is compatible with systems that use REST API. It is compatible with Microsoft Azure as well.

It also offers customized solutions. There are multiple tutorials available for people who are new to the IoT and Unidots’ platform.

8. AWS IoT Analytics

AWS is another IoT platform from Amazon Web Services. It collects a large amount of data from devices and stores them. You can run complex analytics to reveal or answer the query you input.

A unique feature of AWS IoT Analytics is it cleans and filters data received from sensors. It enriches the data and runs analytics. You can run queries using the inbuilt SQL query engine. Using AWS IoT Analytics, you can know which users are most likely to stop using their wearable devices.

9. Azure Stream Analytics

Azure Stream Analytics is a product of Microsoft, it integrates with Azure IoT Hub and Azure IoT Suite. It features real-time analytics on data from devices and has real-time analytical intelligence. It processes data from devices and displays results with Power BI.

10. Ayla Insights

This IoT platform is a product of Ayla Network. Ayla Insights is a powerful tool that fully integrates business intelligence and analytics. Its target markets are manufacturers and service providers.

It allows organizations to see how their products are being used. It requires no extra software to function – it is a fully integrated system.

11. Watson IOT Platform

IBM Watson uses cognitive computing to give its users deep insights into their data. Watson allows users to receive data from devices, run complex analytics, and produces great visuals. It is a cloud-hosted service, you’d connect and register your devices.

It allows its users to securely receive data from devices and sensors connected to the Cloud.

12. Cisco IoT Cloud

A platform owned by Cisco. Its target markets are manufacturing, energy, transportation, smart cities, government, healthcare, and more. It obtains data from sensors, stores, and performs complex analytics.

13. Google Cloud IoT

Google Cloud IoT

Google Cloud IoT offer fully managed IoT services. It is a fully integrated platform where you simply connect your device, manage it, get solutions to complex problems, and visualize your data in real-time. It also gives room to make operational changes. It can automate responses or allow you to take action as needed.

Google uses Cloud IoT Core to obtain data from devices. This data is stored on Cloud Pub/Sub. Google BigQuery allows for quick queries and insights. Cloud Machine Learning Engine runs advanced analytics as well as machine learning. Google Data Studio publishes the result on its rich dashboard.

This platform works well with Android, it also supports devices from Intel and Microchip. Its target market includes manufacturing, utilities, smart transportation, oil and gas, and more.

14. Autodesk Fusion Connect

Autodesk Fusion Connect is an IoT solution from Autodesk. It claims to be the leading enterprise-focused IoT platform. It allows two-way communication with devices in the field. This allows the user to monitor, analyze, and remotely controlling their devices. It also gives information on device maintenance, which ensures lower downtime.

The platform is easy to use and allow just about anyone to configure their devices, control them and build custom connectivity solutions for machine-to-machine (M2M).

15. SAP Analytics Cloud

SAP Analytics offers its users with cloud connection, real-time analytics, ad-hoc queries, and collaboration tools. It uses in-memory technology from SAP HANA. It uses machine learning to make predictions and future trends.

In conclusion, the most beneficial features in any IoT platform are user-friendliness, connectivity, real-time updates, data processing, and visuals or notifications. Before choosing a platform to go with considering its usability. As an entrepreneur, it is also important you consider cost and computing power. However, the IoT platforms and devices are becoming cheaper.

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