10 Internet of Things data analytics opportunities
If you aren’t familiar with the Internet of Things (IoT), then it is time to learn. Essentially, IoT is the culmination of using tracking and data transmitting to gain huge amounts of data points for analysis. A simple example would be tracking social media check ins to monitor dining experiences. In reality, investment in IoT is blooming, and the potential for returns is staggering. Here are 10 blossoming fields that are innovating ways to make IoT work.
The obvious starting point is to analyze trends to see what products and providers are producing the most orders. Analysis can go much deeper. UPS has already moved to put sensors on every vehicle. They are monitoring average speed, fuel consumption, emissions and wear and tear on their vehicles. They are optimizing delivery routes far beyond previous endeavors and they can anticipate vehicle downtime, using predictive techniques and preventative maintenance to avoid breakdowns. Lowering the cost of shipping opens up additional investment opportunities that can help UPS, or other shipping companies, expand farther than ever before.
You can imagine some of the crossover analysis between shipping and transportation. In grounded transportation, routes can be optimized against traffic patterns, minimizing idle time to further improve fuel efficiency. Tracking transit trends also helps reduce wait times for passengers by supplying more popular stops with sufficient service. Mostly, travelers can improve experiences when IoT data is mapped in useable ways for them. Giving individuals more power to plan their own trips puts efficiency in their hands, and it has proven extremely effective so far.
3. City Planning
Barcelona has already started pioneering uses for IoT. Using wi-fi enabled parking meters, they can provide residents with updates and recommend parking. More advanced analytics can lead to better traffic management. EMS can be optimized for better response times, improved deployment and setting service ranges for fire stations and hospitals. Infrastructure management also has a bright future as the massive increases in data can predict maintenance and relief schedules that minimize disruption.
Tying in closely with city data, utilities stand to benefit just as much. Electricity providers can save resources by anticipating power needs and cycling power production accordingly. They can also jump on the planned maintenance train and manage downtime much better. Taking things a step further, increased data output will give them faster responses to outages and help them ascertain the scope of a problem in real time as it happens. Response teams can spend less time diagnosing and more time repairing.
Your first thoughts might lend towards tracking foot traffic into a store to see when and how promotions are successful. You can pair that data with conversion ratings to better improve in-store displays and sales efforts. These methods can be further refined by using targeted special offers. When a customer enters a store, an automated system can push promotional notifications to their phones, and those promotions can even target an individual based on their buying trends. This hits the two major focuses of retail: increasing traffic and improving conversion rates.
Humanity’s oldest trade still has plenty of room for improvement, but it requires extensive levels of data mining. Improvements at this point stem from monitoring atmospheric conditions, soil composition and even solar radiation. John Deere has already put a huge foot forward by putting sensors on their farming equipment that can read all of these things. Farmers can optimize moisture, lighting, weather protection, pest defense and harvest times. Reducing crop loss/risk is the best way to save costs and improve production, allowing for increased diversity in what is grown.
If farmers are already monitoring more weather points, what about scientists in the field? There are two separate branches of weather science that both benefit from the same data tables: meteorology and climatology. Those interested in real-time weather predicting need many more nodes to gather better information. IoT offers those nodes and open up levels of understanding weather patterns that were before unattainable. Likewise, climatology suffers from an extreme lack of good data. Improving worldwide climate models is difficult, as reliable data has been gathered for too short a time. That makes it increasingly important to reduce margins of error on any new points that are collected, creating a need for IoT.
8. Amusement Parks
Major parks in the U.S. see tens of thousands of visitors every day. The industry has pushed a large number of technologies, but the data gathering of IoT is their biggest boon yet. Wearable technology can be used by visitors to give them access and control to many park features while simultaneously transmitting important information. While guests are enjoying controlling lockers or scheduling rides on popular attractions, analysts are able to observe foot traffic patterns, spending patterns and potential safety issues. Improving how a park handles traffic enables them to accommodate more guests and better manage inventory. It also optimizes staffing to save on personnel costs without sacrificing safety or comfort.
Health trackers have been a huge contributor to the push for more IoT developments. Fitness monitors, weather on a phone or wearable, are wildly popular, and they are giving health analysts more data than ever to understand trends, risks and solutions to everything from battling obesity to preventing the next major infectious outbreak.
On the flip side, hospitals and healthcare facilities can use the same analytical techniques as other industries to improve staffing, equipment management and accessibility. They can pair these techniques with digital medical records to streamline inpatient care and reduce potentially fatal wait times. They can also alleviate doctor shortages and reduce human error in record management by automating as much of the process as possible.
Measuring supply and demand is only the first step. Much like these other industries, manufacturers can optimize maintenance routines to prevent costly stops in production. They can also improve storing and shipping schedules. By analyzing more than just the flow of products, every aspect of the manufacturing process stands to enhance its efficiency, and when all of those pieces come together, operational costs stand to drop significantly.
As you can see, IoT data mining and analysis can apply to any industry. Whether a group is just starting or working globally, there is hardly an aspect of any company that can’t improve with these tools. The largest barrier of entry is introducing enough devices to collect and transmit all of the interesting data available. This of course only presents yet another interesting opportunity for IoT. Using IoT to analyze its implementation could potentially remove some of the startup burden that is almost the only thing slowing it down.