IoT Data

IoT data (Internet of Things) relates to the information collected from sensors found in connected devices. It's mostly used by product teams and surveillance firms e.g. in user research and security monitoring. Datarade helps you find the right IoT data providers and datasets. Learn more →
Find the right data, effortlessly.
Discover, compare, and request the best iot datasets and APIs.
Our Data Partners
Subpico Datasets for Real-Time Machine Learning (Global Data Coverage) 249 countries covered icon
249 countries covered
Subpico Datasets for Real-Time Machine Learning (Global Data Coverage) 2 days of historical data icon
2 days of historical data
Our global datasets provide the necessary training info for real time machine development and deep learning (neural) network communications projects.
Automaton AI Car Dashcam Data (for road safety, autonomous driving) 4.4K Images icon
4.4K Images
Automaton AI Car Dashcam Data (for road safety, autonomous driving) India covered icon
India covered
Dataset including road environment like traffic, vehicles, lanes, signals, accidents, directions, etc.
Wikiroutes Global General Transit Feed Specification - GTFS Data Manager (Worldwide Transport Data) 240 countries covered icon
240 countries covered
Wikiroutes Global General Transit Feed Specification - GTFS Data Manager (Worldwide Transport Data) 10 years of historical data icon
10 years of historical data
User-friendly editing tool to operate the database of public transit routes and convert them into GTFS data. Allows database versions, provides analytical to...
Show all →
datarade.ai - Automaton AI profile banner
Automaton AI
Based in India
Automaton AI
We are a full-stack AI company with a mission to democratize Data. Automaton AI is an AI industry expert who is Transforming how businesses see the world wi...
datarade.ai - Subpico profile banner
Subpico
Based in Australia
Subpico
We supply live datasets for real time modeling and application retraining.
100%
Real time
Global
Foot print
All
ML Classes
Wikiroutes
Based in Russia
Wikiroutes
WikiRoutes is a Public Transit Platform that provides data worldwide. Database contains key information for ITS (Route and stops attribution, Transport ty...
> 1.6K
cities covered
3M users
per month
5M stops
globally
Show all →

The Ultimate Guide to IoT Data 2021

Learn about iot data analytics, sources, and collection.

What is IoT Data?

The introduction of the Internet of Things (IoT) has brought about a revolution in the data industry. This is all thanks to a range of sensors and other devices (think of security systems, smart TVs, smart appliances, and wearable health devices) that we are surrounded with. All these devices and technology, connected over the internet, detect, measure, and send data in some form.

In addition to personal devices, there are various commercial IoT devices as well, like traffic monitoring devices, commercial security systems, and weather tracking systems that keep on sending and receiving data. The data collected by IoT is valuable and provides real-time valuable insight.

A few major types of data collected by IoT devices include:

Automation data
The automated lights in your office, the automation settings of your thermostat and the like – send and receive data. This data can be used to study the pattern as to when do lights switch off and on, what is the average temperature that people prefer to have, and so on.

Status data
This is the most basic type of data collected by most IoT devices. This data is collected as raw data and then used for complex analysis.

Other kinds of data provided by IoT devices include log files, mobile geolocation data, video feeds, product usage data, and so on.

Who uses IoT Data and for what use cases?

IoT data is more valuable than ever. It is finding varied use cases in varied industries:

Consumer product usage analysis
Businesses are using IoT data to analyze information about how consumers are using their internet-connected products. For instance, Birst used the IoT data collected from internet-connected coffee makers to estimate the number of cups of coffee brewed by customers per day.

Services for product redesign
IoT data provides you with critical inputs that can be used to redesign, adjust, and customize operations and processes across industries. Abu Dhabi, for instance, recently enabled an adaptive traffic control system that uses real-time IoT data obtained from sensors and trackers on the roads to prioritize the passages for emergency vehicles and ambulances.

Other possible use cases of IoT data include surveillance and safety, better communication with business users and so on. IoT data is also used in manufacturing for factory automation, locating tools, and predictive maintenance.

What are typical IoT Data attributes?

IoT data is highly dependent on the sensors, processors, and other technical equipment. Here are some example data attributes of IoT data:

  • Real-time GPS asset tracking including the position of objects, and maps
  • Energy and environment monitoring including temperature, pollution levels, and air-quality index
  • Health monitoring including pulse rate, blood pressure, and body temperature

How is IoT Data collected?
Majorly, IoT data is unstructured. This is why it can be easily stored in the public cloud infrastructure. Most businesses that collect IoT extract the data from IoT devices and feed it into cloud storage technology.
In the entire process of IoT collection, two things play an important role:

Device management
This includes taking care of device-centric requirements like updating operating shells, registering devices, authenticating identity and access.

Event processing
This takes care of the processing of data events. This aspect takes care of the actual delivery of targeted data points and the like.

IoT data combines the insights obtained through the traditional approach and combines it with data warehouse mining and real-time telemetry of data points to drive results.

How to assess the quality of IoT Data?

There are various dimensions on the basis of which you can determine the quality of IoT data. Here, let’s focus on the most important ones:

Accuracy
Do the data collected by IoT devices reflect the true picture that was produced by each device? For instance, if 10 devices within the same room are reporting the temperature – are all of them reporting the same temperature or is there reasonable deviance between each of them?

Completeness
Are all the data values collected in the big data environment? Are there any gaps in the sensor values or reported events that are missing?

Timeliness
Are all the data values captured in a reasonable time frame? If data is extracted from a range of devices, are there any monitoring points to ensure that all the data is properly synchronized?

How IoT Data is typically priced?

More often than not, IoT data is sold on the basis of the following models:

  • The buyer conducts a reverse auction in which sellers provide their asking prices. The buyer then tends to go with the seller with the best price to coverage ratio.
  • Based on data volume. A certain amount of data is free per month, and after that, a certain fee is charged.
  • Some vendors also charge based on the quality of data. The data that is properly cleaned and ready for an analysis of costs and more.

What are the common challenges when buying IoT Data?

IoT has made the entire process of data collection a simple task. With the advent of sensors, devices, and other things that can be connected to the web, there are lots and lots of data surrounding us. However, more data means more complexity.

If you are out in the market for buying IoT data from an IoT data vendor, it is likely that you will come across a range of challenges.

Complexity
IoT data is complex. Most IoT data providers do not provide timestamps or geotag data. This adds to the complexity of data and makes it difficult for you to process it.

Huge volumes of data
According to estimates, there will be more than 41 billion connected devices by 2025 generating 80 zettabytes of data. With so much data all around us, it becomes difficult to choose the right IoT data provider that could meet your end-requirements.

Interoperability
Although IoT data is readily available, it is difficult to integrate it with other business applications and data repositories.

What to ask IoT Data providers?

  • Before buying data from an IoT data provider, here are a few questions that you should consider asking:
  • From what different IoT platforms are data collected?
  • What types of IoT data analytics are available?
  • In what format will the IoT data be shared with you?
  • Is IoT data provided in line with the recent rules and regulations?

You might want to ask other questions as well, depending on your use case.

Who are the best IoT Data providers?

Finding the right IoT Data provider for you really depends on your unique use case and data requirements, including budget and geographical coverage. Popular IoT Data providers that you might want to buy IoT Data from are Automaton AI, Subpico, Wikiroutes, Freckle IoT, and Adbrain (by The Trade Desk).

Where can I buy IoT Data?

Data providers and vendors listed on Datarade sell IoT Data products and samples. Popular IoT Data products and datasets available on our platform are Subpico Datasets for Real-Time Machine Learning (Global Data Coverage) by Subpico, Automaton AI Car Dashcam Data (for road safety, autonomous driving) by Automaton AI, and Wikiroutes Global General Transit Feed Specification - GTFS Data Manager (Worldwide Transport Data) by Wikiroutes.

How can I get IoT Data?

You can get IoT Data via a range of delivery methods - the right one for you depends on your use case. For example, historical IoT Data is usually available to download in bulk and delivered using an S3 bucket. On the other hand, if your use case is time-critical, you can buy real-time IoT Data APIs, feeds and streams to download the most up-to-date intelligence.

What are similar data types to IoT Data?

IoT Data is similar to Telecom Data, AI & ML Training Data, Automotive Data, Research Data, and Cyber Risk Data. These data categories are commonly used for Data Science and IoT Data analytics.

What are the most common use cases for IoT Data?

The top use cases for IoT Data are Data Science.