Thursday, April 6, 2017

TECH | "Demon net" iPhone app prototype

The following is a video demo of the first prototype of my new iPhone app that uses its video camera to collect data on demonic activity it detects; it does this by comparing variations between two like images as measured by certain key metrics that quantify image quality. One image is made in real-time and is constantly replaced by a new one while the app is at work; the other is a copy of the very first image acquired when the app was launched, and is never replaced unless the phone is repositioned or moved:

The demo shows the app collecting peak signal-to-noise ratio data 30 times a second (in the graph), while updating the database (in the table) once a second. The PSNR is an image-quality metric that measures variation between two images that are, ideally, supposed to be identical and made in an environment where light levels are stable and there is no motion within the purview of the camera; the camera must pointed in the same, exact direction and locked in a perfectly still position when each image is made. Each PSNR value is calculated using the results of a comparison between the current video frame (captured by the iPhone camera while it is stationary), and the reference frame (captured whenever the iPhone is moved).
NOTE | I need to fix this; should be after the iPhone has stopped moving after having been moved—not right after it detected movement, as it does right now. As you can see, though, while the prototype looks pretty basic, it has built-in, automated assurance that the data it acquires cannot be skewed by user error, and that without their interaction of any kind.
Obviously, the video frames change constantly, while the reference frame never changes unless the phone is moved. When that happens, subsequent video frames could not possibly be identical to the reference frame, which would distort the data, and possibly yield a false positive; the app does not record any data generated unless the phone is stock still, and the reference frame is an exact copy of the first frame since the phone stopped moving.

The concept of using image-quality data to detect cloaked demons was first introduced in TECHNOLOGY | Detecting (real) demonic activity in digital media; it provides details on which image-metric variances specifically indicate the presence of hidden demons using nothing more than a digital camera sensor, and shows how it could be done with consumer-level image-processing software available online for free.

For those interested, the PSNR is calculated using the same C++ implementation algorithm provided for PSNR on the OpenCV site, the makers of the software used in the app for image processing; although, that is not the only way to calculate that image metric, and is not how many others do.

About data privacy and disclosure
The app sends the data it generates for storage in a secure, centralized database hosted by the largest, most widely trusted third-party data server hosting provider in the world, which does not contain any information that can be used to identify users. The data consists of only the PSNR measured every one second, the time it was measured, and the GPS location of the iPhone when the frame was acquired. The results of the data as a whole will be published and otherwise made accessible to anyone; however, the PSNR values collected by an individual user will never be revealed, but will be replaced with non-specific-but-descriptive words to indicate their relevance as a collection of values from all users, namely, high/low and flat. Images are rendered directly to the screen for display only, leaving no means for retrieval or storage; they are never stored in memory or on the iPhone, temporarily or otherwise.

The app isn't a solution...
The intent is not to warn people of demons using an app; if you're human, and you're reading this blog, you've been warned: you got demons, and they are a problem. The app is the beginning of an effort to remedy the problem—or at least parts of it.'s a means to a solution
Specifically, the app will acquire data for use to ascertain certain specifics on a kind of demonic activity that occurs at night, usually while people are sleeping, and the species involved in that activity; it will be deployed to as many people who can use it, and that in order to collect a sufficient amount of data to accomplish the research objectives (i.e., determine the physical and behavioral characteristics of "night-time" demons and their native realm, and the logistics of their operations are tied to them in order to develop defenses against their violent and predatory behavior. Although each element of data is comprised of only a single image-quality metric, the time the metric was acquired and the location it was acquired, a lot must be acquired in order to reasonably establish essential tactical information, such as:
  • the number in the ranks of the demonic assailants, in order to properly determine and allocate resources for defense;
  • when they work, where they work—not just to determine a time of day according to the human calendar, but also by the several other known methods demons keep time, but to ascertain which of the constraints imposed by environmental, natural, etc., factors that limit the tangible interaction of a given species in our realm that can be identified by the time in which such constraints occur. Here are examples of what:
  • Some demons use the sun to travel the earth, literally riding a twilight zone of sorts to get to one place to another. If my observations have led to the correct conclusion: light can propel certain materials just like wind in a sail, which we all know by that lightbulb-shaped glass tube with the windmill inside it [from science class] that spins when light hits its black-and-white fins. and some demons can cloak to the same properties those materials exhibit in order to propel themselves using light; and, just like the fins of a light mill, they will be pushed by one of the many rings formed by sunlight as it hits a round earth, which are characterized separately by a unique, homogenous degree of heat and light. It's important to be able to anticipate with as much precision as possible when and where a demon enemy will be.
NOTE | Actual twilight is the most visible ring, which is bordered by night; all others are simply bordered by less sunlight.
  • Some demons act only during specific astrological events, like hobgoblin demons, who tend to work en masse during the first quarter phase of the moon. I have seen no evidence that suggests that this is the only time hobgoblin demons can work, nor have I any evidence that suggests it is a more opportune time, other than by the fact that it is widely established, accepted and accommodated by all other demonic species that first quarter is hobgoblin-demon time for certain things that must not be interfered with. Hobgoblin demons were among the first of six species that entertained an offer to unseat the Voices Demons from "door duty," when it was proposed a year or so ago; this tells me that hobgoblin demons carved themselves an exclusive slice of earth time through supremacy of power—not because they had the wind at their backs, so to speak. It's important to know whether a demonic species has the power to pick and choose a time to strike or whether they are at the mercy of Mother Nature, like the weapons-like power inherent to many demons, which waxes and wanes according to the Babylonian Planetary Hour.
Everyone will benefit from the outcome of the research; however, for now, users of the app are simply participants in an effort to collect data for that research. The app provides no immediate value (although the data collection phase is expected to be complete in about a month).

The app as shown captures 30 video frames per second, comparing each one to a reference frame for the specific variations in image quality (color noise) caused by interference to the operation of digital camera sensors. The metric calculated by the comparison (peak signal-to-noise ratio) is stored in the table along with the time it was measured; a graph is also generated to easily identify significant changes in measurements.

This isn't the final design of the app; it simply provides the minimum components necessary to demonstrate the concept, and to show the app's progress.
NOTE | There's only one more function to add, specifically, the transfer of data from the iPhone to a data server.

More about the app on this blog
The app described herein this post collects data for the DemonNet DAQ System. It measures CCD noise in camera images to detect and track cloaked anomalies via their unique EMF interference signature. It also stores the time and location of each measurement. All clients upload their data to a central database, which is then combined to track the anomalies over a wide geographic area.

More information regarding the purpose of the DemonNet DAQ System, and how the data collected by clients will be used for the aforestated purposes, is available on this blog at:

TECHNOLOGY | How to build a demon detector with your cellphone

TECHNOLOGY | Detecting (real) demonic activity in digital media

DIGEST | (TECHNOLOGY) Tips and Techniques for Processing Demonic Digital Media to Save the World

PREVIEW | DemonNet for iOS Developers

Human technology is not always the demonic inferior

TECH | Apple approves DemonNet App for Beta Testing

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