More feedback: sub-band coding is often used & generic radio receiver/transmitter is often sabotaged in the mfg. ready stage to dampen or block the bands with sensitive info. Recs for non-tampered radios are seemingly needed.

Bluetooth LE vs. Zigbee mesh also maps to UK/Russian/Trump vs. US/OhioU tech.

Sources say that undocumented protocols are often low speed digital, like morse code.

Lots of sounds feature an initial percussive/wide spectrum burst & then a more sustained lower frequency interval that trails off. Sources say to look at amplitude modulation in the sustained part of bursts.

Lots of focus tonight on which combos of curl make pleasant sensations versus painful or merely uncomfortable ones. Is it just a matter of technique or are some EMF providing objects suitable while others are inherently unsuitable?

Don’t know. My medium term plan ways always that GT would produce optimal sets of consumer desirable objects/kit & control the networking. The experience there isn’t limited in any way by what has gone before. The arty, pleasant examples that exist are demos of the possibility & promising combinations for research inspiration.

On the other hand, the current world includes many decades of manufactured things that are secretly participating in spy & communication networks, delivering terrorist harassment to helpless target, and sometimes causing fatal autombile crashes. Interacting with those things is very much an issue of what is in place & how to make better use of or mitigate it.

The majority of IoT components are undocumented for the public & focused on EMF harassament & spying. Relaying energy to neighbors is perhaps their most common activity. Each component has a permanent and often dynamic status of how likely it is to pass energy. In the Heine version of coding, it is often trying to direct energy at sensors which say “I am seeing hair” or “I am sensing P”, or “I am sensing EMP attack site” or “I am sensing dampness (could be urine from attacks)”. Some forms of control involve directing signals telling which sites should claim they have a hot target in range to receive energy & emit it at whatever looks most like a target. The radios like Bluetooth LE and Zigbee are sometimes used for this control function, communicating with individual IoT devices or the devices in a particular location. Solid things like metal or hard plastic may have a built in flexion response rather than an EMF emitting response.

Some TI ids are the right type to send/receive longer range signals in the Trump/Russian/UK network. Probably there are databases which map ids to macs and visa versa, but I don’t know the details.

We believe the story that very few if any Zigbee thins don’t come with a secret back door access that can convert them to operating in BLE networks.

Consider the possibility of working out multi-dimensional control in multi-layered semi-supervised systems.

Something like:

High Layer – SMIL 2 Like interface (I mean granularity, not XML syntax) for scheduled events including both presentation & control

Middle Layer – Systems of learned “gestures”

Lower Layer – atomic bits of any BLE primitive of interest with a timing model, probably a digital clock.

The learning system tries to optimize multi-criteria at each level. The basics is like Deep Learning networks, but other algorithms work at making the system more adaptive, reconfigurable, & efficient over time (see recentpaper selections)

Q: How can the higher levels be adaptively structured for learning?

A: For formal/engineering study we have to define problem boundaries somewhere. Conceptually (perhaps about the level of implemented computation), we can pick a Situation Semantics of Objects/Space/Time at some levels of macro granularity which are expressive enough to describe all the conditions we want to model/deal with & precise enough to stand in a fixed probabilistic or fuzzy set relationship to what we can measure about those situations and/or care to use as semantically linked latent variables in modeling. Inside of that, we can define dynamic collections of graphs that represent situations of interet & change between those situations (caused by us, caused by the flow of time, the weather, or whatever…). We can use the language of situations to talk about how the graphs project to isolated sub-problems and what the corresponding graph network looks like there.

For the language of higher level interactions, development should assume that it is eventually moving in the direction of multiple human actors, even if the existing work developed in a reference frame of a single individual.

Informants say that interface usability along with quality & reliability of information & dynamic search protocols is important to the usability of Bluetooth Mesh Networking configurations.

For GT it makes sense to create simulations for BLE and Zigbee mixing that model search/connections of interest in order to work out the best forms of server help/configuration control.

In the IoT implementation of AM style signaling, many micro units are positioned with a certain carrier frequency & phase – think of a filmy hose that pops a bubble at a certain rate & size. A kind of override hacking of the previous program involves directing energy to local positions so their phase changes to something else.

At least that’s the vague understanding I got from my source.

For experimental hacking, it would be desirable to have accurate analog simulations & languages/libraries of software controls with parameters that can be used in gestural/(media show like) semantics to create the effects that have been found to be the most interesting & significant – in some cases this is a sensation of EMF at a particular site & in other cases it’s like changing the RFID labels or directives on particular bits of IoT.

The broad networks of IoT that provide sensor data to search queries are said to include some hardwired satellite type links, analogous to known servers for NTP. The data from the installed base is not encrypted, but drawing large amounts of summary data involves reading those hardwired “up links” using some intermediaries.

Baby Ping learned to control a special radio in a semantic way. Software routines can substitute for semantic control. Signals can have parameters that include:

a) Local semantic coordinates of max signal direction
b) power
c) spread
d) AM carrier freq
e) AM phase
f) Overalayed AM signal (amp, etc)

For receiver body coordinates, signal direction & spread are replace by profile of the sender directions that created “THIS SENSATION” (e.g. right foot tingling)

The Deep State offensive system has been set up to focus on long range cyber attacks via gear that is often controlled/hackable using wireless signals. The main control consoles may be in military or paramilitary bunkers that are the last opponents to reform. In that case, the most practical defense may often involve local position of limited wireless controllers that periodically turn/disable to offensive elements of the gear – e.g. at cable interfaces, utility poles, utility stacks, etc.