Facebook patent to “detect that two smartphones were in the same place at the same time [and] by comparing the accelerometer and gyroscope readings of each phone… identify when people were facing each other or walking together.” https://t.co/P6VSdDV7Xx
— TJ McIntyre (@tjmcintyre) January 11, 2018
Did you sign up to beta test Google Glasses? Have you ridden in Google’s driverless cars? Your answer to both questions is likely not yet, but these are two very interesting innovations coming out of Google X (Google X is a secret facility run by Google thought to be located somewhere in the Bay Area of Northern California) that have been widely covered by the media.
These two innovations demonstrate the combination of mobile communications, the Internet, mobile software apps, all kinds of sensors, augmented reality, artificial intelligence and real time analytics. I think the coolest components of these innovations are rarely highlighted – the integrated sensors that make them possible.
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.
Developments in hyper spectral sensors are being supported by innovations in remote sensing combined with GIS (geospatial information systems) and Big Data analytics. 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.
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.
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.
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 scary, 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.
Google Glasses do not yet have hyper spectral remote sensing cameras built-in, but they do have sensors that are limited only by their physical size and weight, and include augmented reality connected with Big Data.
The world is quickly being documented, digitized and given a digital persona. The digital persona is only as accurate as the sensors that are being used. The more accurate and connected sensors are to Big Data analytical systems, the more the Big Brothers know about us and everything around us.
How about we all work together to ensure that our Big Brothers are good big brothers. What do you say?
Matéria completa na fonte :: http://www.direitodainformatica.com.br/?p=2027