Global Sensor Data |
Just last week I read this about a new iPhone patent, "The patent is titled “Digital camera with light splitter.” The camera described in the patent has three sensors for splitting color. The camera would split colors into three different rays. These would be red, green and blue. The splitting of colors is designed to allow the camera to maximize pixel array resolution." This patent potentially could help Apple improve the image quality of its mobile cameras, especially in video. In other words, it will help iPhones better capture, display and share the scenes on our planet for viewing.
At the Mobile World Congress in Barcelona this year I saw demonstrated an iPhone add-on from the company, Flir. It was a Personal Thermal Imagery Camera. You connect it to your iPhone and then you can find leaky pipes in your wall, overloaded electrical breakers, or even spot live rodents hiding in your walls. You can use it in your boat to spot floating debris in the water in the dark or use while hiking in the dark to spot hidden predators preparing to devour you. I WANT ONE NOW!
Sensors measure and collect data and can be connected to just about any piece of equipment. Satellite cameras are sensors. There are audio and visual sensors. There are pressure and heat sensors. There are all kinds of sensors. One of the most interesting sensor technologies I have been researching of late is hyper spectral remote sensors.
Hyper spectral sensors combined with GIS (geospatial information systems) information and Big Data analytics are a powerful mix. These sensors can be integrated into very powerful cameras. Hyper spectral remote sensing is an emerging technology that is being studied for its ability to detect and identify minerals, terrestrial vegetation, and man-made materials and backgrounds. I want one!
Hyper spectral remote sensing combines imaging and spectroscopy (spectroscopy is a term used to refer to the measurement of radiation intensity as a function of wavelength) in a single system, which often includes large data sets that require Big Data analytics. Hyper spectral imagery is typically collected (and represented) as a data cube with spatial information collected in the X-Y plane, and spectral information represented in the Z-direction.
hyper spectal imaging |
What can be done with hyper spectral remote sensing? Using powerful hyper spectral cameras one can detect unique noble gases (each unique gas emits a unique color on the spectrum), different inks, dyes and paints (each have different characteristics that can be uniquely identified). You can detect, identify and quantify chemicals. You can detect chemical composition and physical properties including their temperature and velocity all with a camera!
Taking a hyper spectral image of an object, connected to real-time Big Data analytics, can tell you an amazing amount of information about it. Theoretically, a hyper spectral image of a person combined with facial recognition can identify a person, their shampoo, make-up, hand lotion, deodorant, perfume, the food they ate, chemicals they have been in contact with and the materials and chemicals used in their clothes. OK, the implications of this technology for personal privacy are really creepy, but the technology itself is fascinating.
Theoretically hyper spectral remote sensing systems can be used for healthcare, food monitoring, security at airports, for public safety, in intelligence systems and integrated with drone and satellite surveillance systems.
Today, luckily, these cameras are far too expensive for me.
Related Articles: http://mobileenterprisestrategies.blogspot.com/2015/04/iot-sensors-tactile-feedback-iphones.html
Related Video: http://mobileenterprisestrategies.blogspot.com/2015/03/iot-and-sensors-from-ams-at-mwc15.html
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Kevin Benedict
Writer, Speaker, Senior Analyst
Digital Transformation, EBA, Center for the Future of Work
Cognizant
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***Full Disclosure: These are my personal opinions. No company is silly enough to claim them. I am a mobility and digital transformation analyst, consultant and writer. I work with and have worked with many of the companies mentioned in my articles.
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