LOCATING SUCCESS

Everywhere we move, we are connected with our phones.  We use our GPS to find our way around town and include our location in social media posts and messages.  We are always connected and through this we create large amounts of data every moment.  Amazing value for business can be created by tracking swarms of people and analyzing the data through readily available technologies.

Big Data from Cheap Phones

Kenya Malaria Sources

Data collected from cheap phones can help grow business by providing insights into human movement and behaviour.  To illustrate, consider Harvard School epidemiologist Caroline Buckee who uses cell phone towers in Kenya to track the spread of diseases.  She does this by cross-referencing location data that the infected persons have in common.  The data is entered into a predictive modeling program that layers points over satellite imagery to highlight possible hotspots for the infection sites of malaria.  In the first test run they found a busy tea plantation to be the breeding ground for millions of malaria infected mosquitoes.

In another example a France-based global telecom giant released anonymous cell phone data for five months’ of calls made by five million people in the Ivory Coast.  This raw data was used by many to create innovative uses for the data such as one company that built a transportation model of bus and taxi ridership.  Armed with location information on swarms of people, companies can make decisions based on information instead of more risky alternatives.

Collecting your own Data

At this point, getting the data from other cell phone providers may prove difficult and so there are other methods to collect this valuable data including sniffing for a smartphone indoors and data crowdsourcing.  There are a vast number of methods to sniff locations of smartphones including triangulation using WI-FI, Radio Beacons and even smartphone apps that relay sensor information.  This anonymous location information can be accurate to within a few meters.

Using this information a business can see where shoppers are spending the most time looking and places that they skip past.   As a result, planned business integration with a smartphone app like Mobile Bandit could notify shoppers of complimentary products nearby.

Indoor tracking technology has so much potential that Google executive Don Dodge has commented on integrating indoor tracking for google maps.  Another form of accessible data collection is through data crowdsourcing.

To illustrate, a research firm in Australia is developing noise maps based on data crowdsourcing.  The team released an app for smartphones that monitors noise levels and uploads the data to mapping software in near real-time.  Imagine using the same technology to find out where a targeted demographic of people swarm during the summer and more.

Visualize Data Success

Data is relatively useless without a way to visualize the information.  Recently super computers have been used to sift through the huge amounts of data fast; now this can be done using everyday computers.  MapD (massively parallel database) uses the graphics processing units (GPUs) in an everyday computer to process huge amounts of the data in milliseconds.

The technology was first used for Twitter to process tweets in near-realtime and find trends based on the location of each tweet.  In the video example just below, you will see a search for the tweeted word “rain” flash all throughout the world map.  In the past these searches would take seconds and up to minutes.

Useage of MapD has already been adopted by the Sunlight Foundation which sifts through the data from 20 million donations categorized by donor, region or elected official.

Nvidia, a leading manufacturer of GPUs has recently announced plans to demonstrate MapD using eight GPUs on more than one billion tweets at an upcoming event.  By using this technology huge torrents of data can be analyzed for useful business information 70 times faster than previous methods.  Click the following link for a real life example of MapD.  http://mapd.csail.mit.edu/tweetmap/

Conclusion

Many people are concerned with privacy regarding location data, however we are all giving up privacy for convenience and “free” access to useful applications.  That being said, some of the technologies such as WiFi triangulation are anonymous and non-intrusive (Home Depot uses this).  There are some exciting advancements in location technology.  While this area blindly grows there will be some hugely successful technologies.  Technology in location data has advanced enough to get your business involved today.  There is every sensor you need built into today’s modern smartphones. Whether you design consumer apps to sell data to businesses, or utilize location information for your own venture it can create a lot of value when done right.

References

ArXiv. “Noise Pollution Maps Crowdsourced from Smartphone Data.” MIT Technology Review. N.p., 22 Oct. 2013. Web. 17 Nov. 2013.

Kopytoff, Verne. “Stores Sniff Out Smartphones to Follow Shoppers.” MIT Technology Review. N.p., 12 Nov. 2013. Web. 14 Nov. 2013.

Talbot, David. “Big Data from Cheap Phones.” MIT Technology Review. N.p., 23 Apr. 2013. Web. 17 Nov. 2013.

Talbot, David. “Graphics Chips Help Process Big Data Sets in Milliseconds.” MIT Technology Review. N.p., 16 Apr. 2016. Web. 16 Nov. 2013.