There has been a big change in the way data is collected about our environment. Companies are seeing the benefits in mobile devices as now most people have a smartphone of some sort. Analysts are moving away from using specialist equipment that cost millions of dollars to install and upkeep and using apps or social media as a way of gathering data.
If you look at a major highway in Google Maps you will notice live traffic information. It shows with a color coding system how fast the traffic is moving along that section of road. It also allows them to accurately predict travel times between two points or adjust routes to cut times when navigating.
How do they do this? Well all android based phones (that have been set to allow Google to collect location data) are sending GPS coordinates of the devices location back to Google. This allow them to then determine how fast the phone has traveled between two points, which is then compared against normal travel times to determine whether traffic is flowing normally or not. Using one phone to update the traffic conditions is not accurate at all but if you have 100 or more devices travel through the same two points then a clear picture can be built of what the conditions are like.
This is are much more affordable and simpler way than installing cameras or detection devices on all roads, motorways and highways and having them monitored. Not only this mobile devices are world wide already and the amount of devices is growing in more locations. This means it is easier for Google to expand its Maps service.
This service by Google has been around since 2007 so it is a relatively old service but its reliability and feature set has greatly improved since. It has also become more integrated within the new versions of Android OS.
There are a few new innovations that have joined the smartphone data gathering philosophy recently. One I have found is Sunshine. This is Apple iOS based app that uses data collected from Apple devices and multiple user input to predict the weather. Data from new Apple iPhones biometric sensors is combined with traditional weather predictions (although they are relying less on this) to give increased localised accuracy to the weather forecast for that day. Users can also input what the weather is like at there location adding to the accuracy. If this app is released to Android based smartphone devices too then the data set and would increase. This innovation is pathing a way forward for weather forecasters.
There are uses for Social Media too in environment data collection. Twitter is now becoming a faster source for information than government organisations. The US Geological Survey (USGS) has noticed this when there is an earthquake in almost any location. The USGS has more than 2,000 sensors, mostly based in the US, but what happens when there is and earthquake outside of where the the sensors are located. Well they have turned to Twitter.
It takes less than 30 seconds to post a Tweet and if there is an earthquake there is likely to be thousands of Tweets in a matter of minutes. The USGS now monitors Twitter looking for a set of keywords within a set of parameters to detect earthquakes. In tests that have been run with recent seismic events they it has been found that usually they can be alerted to an event using data from Twitter within 2 minutes. In 2014, the USGS was alerted to the earthquake in Napa, California in 29 seconds using Twitter data, which was before the earthquake shaking had reached some locations.
New innervations like this, I believe, are going to take over from traditional data collection methods. They are not only are they faster but also, most of the time, more accurate and can be extremely cost effective.