By Anne Taylor
This article was originally published on December 7, 2018, on The Data Incubator.
With the evolution of sensor, mobile, and wireless technologies, there’s no doubt that the Internet of Things (IoT) is slowly rising to the apex of modern technology. The true use of IoT, however, lies in the world of analytics – rather than hardware innovations. For businesses, IoT analytics are of crucial importance. Extracting rich insights from IoT-related consumer products helps businesses alter their strategies or better understand the consumer experience.
What’s so great about IoT analytics?
The first thing to realize about IoT data analytics is that it involves the use of sensors for data collection. Sensors are really cheap these days and are sophisticated enough to support a variety of use cases. Data analysis and data pattern recognition are important analysis tools that are used after the sensors have done their part in providing the raw data. Now, the ultimate goal behind IoT is not just fancy data. The goal is the usage of said data to understand people.
Businesses now need more than an online presence in order to flourish. They can hire PHP programmers and have a top-class eCommerce store with amazing features but businesses rely on sales to exist, and to improve those sales you need data from customers. Seeing things from their perspective can prove useful for your business in the long run.
This article discusses some of the use cases of IoT in various industries. It’s important to note that these aren’t the only applications of IoT, there are many more. The value of data collected through IoT, with the help of the following use cases, can help people and businesses better understand IoT’s general impact.
Case #1: Consumer Product Usage Analysis for Better Digital Marketing
IoT has the ability to revolutionize businesses and the way they perceive their customers. In fact, it’s already happening. IoT is helping businesses gain more insights on how consumers are using their digitally connected products. Birst, a self-service analytics solution, is a good example of IoT analytics. Birst gathers data from internet-connected coffee makers and transmits information on the daily consumption of coffee. The data, once connected with data from their social media helps to determine whether the consumers who consume more coffee are more likely to discuss the brand on social media platforms. On the vendors’ side, they can check the variations in the amount of coffee brewed by consumers and how it corresponds to the number of coffee capsules sold by the vendor.
For business owners, the goal of IoT should not just be the introduction of a new line of internet-savvy products. They should also consider the data collected from the products to gain marketing insights, and how business operations are progressing.
Case #2: Serving Consumers and Businesses with The Same Data
The data gathered from IoT has the potential to be used for both businesses and consumers at the same time. Let’s take the example of an IoT for home utilities, like an energy meter. The data collected from said IoT is sold to local and state governments within a country, who then use it for both revenue collection and fraud detection. On the consumer’s end, the same analytics can be used to help them manage and check their energy consumption.
In this case, businesses generate value from analytics in two different ways:
- Data-mining for fraud detection.
- Providing services for consumers that are both cost-effective and sustainable.
Case #3: Using Data From Sensors and Camera-Enabled Devices
The field of social analytics is, perhaps, one of the most exciting domains of IoT. It involves the use of multiple data sources to gain actionable insights into user behaviors. The phenomenon is referred to as “connected events”. Connected events are large-scale sensor deployments that help in understanding user behavior. The sensor enables analysis of human emotions rather than using device imaging. More commonly, it is akin to the field of sentiment analysis. A good example of this is the use of a heat-map of spectators during a sports game. Combined with other sensors and game data, we can gain an understanding of spectator sentiments during the game.
Case #4: IoT Data Analytics for Surveillance and Safety
Infrastructure protection is an important business consideration in order to guarantee employee safety. Companies such as AGT International use IoT to protect their oilfield infrastructure through the deployment of camera and motion detection sensors. In the context of infrastructure protection – specifically for machines – human intuition can be bested through the use of AI. This is where IoT devices come in with their fault detection capabilities. AGT’s traffic management solution, because of its machine learning prowess, figures itself out, which helps non-technical operators to write complex rules for an event. The self-learning aspect of this traffic management system is based on movements detected through video signals. Any sign of an accident will have the impact of triggering an alarm. Traffic management operations like these are useful for machinery maintenance and adjustments, which in turn, ensures employee safety.
The focus of any business should be an effective analysis of user-data, not just product innovations. The technologies behind IoT platforms deal with specialized forms of data processing to deal with real-time datasets generated with the help of sensors. The four use-cases discussed in this article are just the tip of the iceberg, IoT has and can have a lot of influence on present and future businesses. The best thing about IoT is the diversity it provides for businesses. Regardless of whether you are a military organization or an IT company, you can benefit from the uses of IoT within your respective organization.
