Three applications of M2M and Big Data
By Will Kelly
January 16, 2013, 11:18 AM PST
Takeaway: Will Kelly points out three areas where Machine to Machine (M2M) technologies and Big Data are coming to together to deliver business results.
Machine-to-Machine (M2M) technologies otherwise known as the “Internet of Things” brings with it a varied history of success. However, we are starting to see where M2M and Big Data are coming together in this past year to deliver some impressive benefits across a number of industries.
Big Data revolves around customer behavior and M2M devices typically small wireless sensor devices could be the ultimate tool for capturing customer behavior whether it be their location, energy consumption in their home or office, or how hard they applied the brakes on the way home in traffic. The combination of Big Data and M2M has the potential to elevate both technologies into wider and more innovative uses as the following example of M2M and Big Data shows.
Wireless carriers
Wireless carriers are a natural market for M2M and Big Data solutions because their business is data intensive primarily due to calling and data usage tracking. There is also the prospect of value added services for targeted markets such as healthcare and location intelligence driving wireless carriers to M2M and Big Data solutions.
One example of an M2M and Big Data monetization options for wireless carriers is Spacecurve, a startup got some buzz last fall around its soon to be launched location based services for wireless carriers. A wireless carrier could put the Spacecurve technology to work improving its market and service quality from the location information it captures and then analyzes.
Better energy management
Today’s economy is making better energy management an imperative for consumers and businesses alike. M2M brings the wireless remote sensors and Big Data brings the data storage and analytics to the energy game that helps build out reporting and analytics systems that were out of reach just a few short years ago. The combination can watch for trends in peak energy usage delivering actionable information on how energy costs can be reduced.
M2M and Big Data are becoming a popular trend at the Smart Grid level as referenced in the recent Smart Grid Trends to Watch: ICT Innovations and New Entrants post on Smart Grid Librarywhich touches upon Smart Grid applications such as revenue assurance and voltage conservation.
Drill down another layer from the smart grid, Big Data and M2M can also help commercial and industrial buildings to save power. A recent IMS Research report about intelligent building trends delves into the cloud and Big Data as the perfect storm for building analytics. With the proliferation of wireless M2M sensors and Big Data analytics, IMS Research could be pointing to a future that large commercial and especially United States federal government office buildings could enjoy to save on costs.
M2M and Big Data Analytics could be the energy conservation tools of the future as the technologies trickle down from the smart grid, to large buildings, and eventually into consumer households as smart thermostats, smart homes, and increased utility company service targeting energy savings in the home take hold.
Auto insurance
During my recent explorations into M2M the one potential application that I find very big brother is M2M and Big Data and how the auto insurance industry can use it to monitor automobile that its customers drive. While fleet management is a positive use of M2M to better route business vehicles for better customer service and fuel savings, an auto insurance company monitoring their customer’s good driving or lack there of using an M2M device that wirelessly transmits data back to the insurance company for later reporting.
An October 2012 Information Week article entitled Where M2M and Big Data are headed gives the example of Progressive Insurance and their Snapshot device, which plugs into a car’s diagnostic connector for tracking driving habits over a thirty day period. The device dishes up details to Progressive including how hard the driver brakes, number of miles driven, and how often the car is driven between 12:00 am and 4:00 am. While installing the Snapshot device is completely voluntary, the short list of what it tracks, speaks to the role of Big Data and the potential volume of data that an insurance company could be capturing and storing on the individual customer, and their customers on a per city/town, state, and even regional level.
The combination of M2M and Big Data can help auto insurance companies make informed decisions about their customers, based on their driving behavior. However, there is no way around not calling the M2M and Big Data potential in the auto insurance industry invasive on personal privacy. The resale and court subpoena value (even for non-traffic cases) on this data should also be of concern if such devices move from voluntary to the rule.
Conclusion
With M2M technologies maturing and becoming increasingly available, it’s certainly on the cusp of becoming another technological element of the current Big Data revolution we are experiencing. Each of the examples in this post show how M2M and Big Data can be applied.
