The one-pixel camera is a strange alternative to regular cameras.

"Kobe University YONEDA Naru and his team could adapt their setup to construct a microscope that can record a holographic movie through a light-scattering object — a mouse skull to be precise." (Interesting engineering, Tiny 1-pixel camera films holographic 3D movies beyond visible light, through objects)

In this text, the "camera" includes digital image-remastering tools from DMD to a computer that creates the image. So, the computer and AI are part of this system. 

Single- or one-pixel imaging systems are strange but effective ways to observe small structures. The single- or one-pixel CCD systems can make 3D images of small objects. The size of the pixel determines the camera's accuracy. Small pixels give higher accuracy. The thing that makes this kind of system effective in nanotechnology is that the observation system itself doesn't transfer energy to the object. And that doesn't bring artifacts, or non-controlled effects to the system. 

The tiny one-pixel camera can be a new and powerful alternative to CCD cameras. The one-pixel camera uses only one pixel to make images of 3D structures. The size of that pixel determines the accuracy of the camera. The system uses singe-pixel imaging which is one version of computer imaging. 

The large pixel means that the system is less accurate than a system with a small pixel. And if the system uses a one-pixel version of the megapixel-class CCD camera. It can make images of tiny 3D structures. 

"Schematic of a single-pixel camera using a DMD. The transmitted light (white) from the sample (blue) is modulated by the DMD and collected by a single-pixel detector. (Wikipedia, Single-pixel imaging)

A 3D single-pixel imaging. 

"A pulsed laser uniformly illuminates a DMD, used to provide structured illumination onto a scene, and the back-scattered light is collected onto a photodiode. The measured light intensities are used in a 3D reconstruction algorithm to reconstruct both depth and reflectivity images." (InterestingEnginering, Tiny 1-pixel camera films holographic 3D movies beyond visible light, through objects)

The system requires a digital micromirror device, DMD, and mirror systems that aim light at the system. The system requires light. And that means it brings a little bit of extra energy to the system. However, the need for energy is much lower than in the scanning systems. 

In that kind of system, the developer must only separate one pixel from the CCD chip. When a one-pixel camera makes images, it just scans the surface. The pixel moves back and forth. Or that pixel can be at rotational toboggan, which allows it to move fast. The system can turn that pixel from one direction into another. 

Making the image of the object. When we think about the ball-shaped system there is a possibility that when the scanner moves around the axle there is a switch that cuts electricity from the pixel, when it's in a certain direction. The system can have three positions. The small-area photographing, and 180 and 360 degrees scanning images. 

The other version is the system where the CCD camera's pixels are connected separately with the microchip. Then the system just connects the pixels to the computer one by one. That gives the system the ability to do virtual movement.

That is possible if the CCD camera's pixels are connected to the computer separately so the system can transform the CCD chip into a one-pixel camera. In that kind of system, the system benefits the CCD chip's ability to handle every pixel as an independently operating camera. 

https://interestingengineering.com/innovation/1-pixel-camera-films-holographic-3d-movies

https://www.nature.com/articles/ncomms12010

https://en.wikipedia.org/wiki/Single-pixel_imaging

Statistics is the ultimate tool and artificial intelligence makes it more effective

Statistics is the ultimate tool and artificial intelligence makes it more effective

Statistics are boring, but the reality is that they are boring only when the data is collecting. They are uncovering many things, and the statistics are telling, are we changing our wheels or tires more often than usual driver, or is our car damaged more often than a regular car. This kind of things is telling something, what we might not want to tell other people.

Statistics is a more ultimate tool if they are connected with artificial intelligence, which can collect data from the things, what are not seen before in the old-time traffick control cameras. Those artificial intelligence-based systems can register also if the vehicle is turning to another lane, without showing flash. It also registers the mistakes in driving in the cases, when the driver is driving following speed limits.

Artificial intelligence also notices if the car doesn't stop before the crosswalk if the walker has put the step on it. This is telling something about the driving style. And artificial intelligence also registers things like does the driver use the seat belt. Those things are interesting data if we would look for a driver, whose driving style is dangerous.

When we are thinking about things like speed limits and changes in lifestyle, we must remember that computers and artificial intelligence can follow things like what the person buys, and if there are changes, that tells that something has happened. The thing is that if artificial intelligence can collect data from different sources, it can find out, is there something, what somebody is hiding. 

If the driving style changes suddenly, there must be some reason for that. When we are thinking of things like artificial intelligence, and what happens when it is connected to the regular surveillance cameras. Those cameras can collect more data, where is seen many more details than using the regular cameras. And how this thing is connected with statistics.

Of course, those cameras can collect data about the driving mistakes, like how many times some driver changes the lane dangerously. The place where that person makes those movements can also be marked, and the thing is that statistics are telling, has someone else make those mistakes in someplace.

This kind of things is really good data if somebody gets tickets for those things because if there are many of certain types of similar driving errors. But if only one driver has been ticketed, would that tell that there is something wrong with that person's relationship with law enforcement.

When we are thinking about the situation, that some person would get a ticket for some minor offense, that tells that the police is tight for this particular person. Especially if this person is only, who has been ticketed. And if law enforcement is tight for somebody, that sometimes means that they are soft for somebody else. This kind of things is really interesting data when there is found real bad drivers and other kinds of exceptions.