I was just wondering if there was any possibility of obtaining RSSI values belonging to Nest thermostats or smoke detectors.
Thanks!
Sorry, but this is not available in the current data model.
Related
Is it possible to calculate distance between BLE-BLE or Beacon-BLE device using Time(T) taken on packet received on receiver device with measured power or RSSI value?
Is there any formula for that?
You can get a formula for estimating distance from time of flight measurements from this paper.
However, commercially available Bluetooth chipsets do not provide accurate timers capable of measuring time of flight. Further, smartphones do not provide access to such time of flight data. As a result, such a formula is if little practical value for most use cases.
I wanted to know if there is any efficient way of finding the distance between 2 devices(a transmitter and a receiver) which is accurate to atleast the order of a couple of inches.
I am basically want to detect the movement of the transmitter from the receiver and how far it has moved from its original position.
I was thinking in terms of using a wireless hotspot/bluetooth connection. I cannot Use some form of audio/medium which can be detected by humans.
Could anybody help me with this?
To my mind, assuming there is no common synchronisation signal between the devices, there are 2 differents way to do this (not really easy):
1. Measure received power : some receivers provide RSSI (Received Signal Strength Indication). RSSI is a measure of how much power you received. If you know the transmitted power, you can estimate the transmission loss (from the transsmission channel) by taking different measure of RSSI at different distance. It will really depends on the channel (environment, frequency, throughput, ..), so don't change it for the measure. Once you got enough points, try to fit it by a curve. You can now predict distance by having RSSI.
2. Measure round trip time : this is called RADAR, and is really more difficult but is the classic way to measure distance and speed. Broadband systems (like WiFi) are better for this kind of measure. By the way you also can do the same with audio for short distances (SONAR), without being detected if you use frequencies higher than 20kHz.
We are trying to stream data from a car's OBD-II protocol via Wireshark. It's working fine and we get the IDs and data payloads out interpreted as CAN. However, we would like to take it a step further and "scale" the data according to the documentation on wikipedia.
This requires that we can use a formula that is dependent on information contained in the ID and in the start of the actual data message.
Could anyone provide some guidance as to how we can create such a scaling/conversion of the data into readable output using Wireshark? Ideally we would also like to inform the viewer of what data, units etc. they're looking at - we have all this info, but we would just need to find a way to return it depending on the ID.
Hope you can help - it would be much appreciated! Martin
I recommend obtaining SAE J1979 and SAE 1979DA. In there you will find the complete information necessary to dissect the protocols, including units and scaling / offset for every standardized PID. Then, codify this into a dissection protocol in Wireshark.
What would be the best way to triangulate a wireless network passively. Are there tools available? Algorithms? Libraries?
My goal would be to create a relative map of various objects that sends or receive signals using signal strength (DB's), signal/noise ratio, signal phase, etc. from a few location points. With enough sampling, i'm guessing it would be possible to create a good 2d/3d map.
I'm searching for stuff in any language / platform.
Some keywords: wi-fi site survey, visualization, coverage, location, positioning
Thinking about using kismet to gather the data and then process it. Maybe Free Space Path Loss for RF in the 2.4Ghz range to calculate a relative distance. And optionally try to use RF obstacle attenuation estimation values (based on some user input) to give better estimates. Then use trilateration to generate possible relative coordinates.
You can't use the GPS technique because the timing is nothing like accurate enough.
The best you can do is Trilateration based on the signal strength from each base station and assume that range is proportional to signal.
You will probably need to force a connection to each base station in turn in order to measure the signal strength.
Interesting question. Initial thoughts were using output from something like the WiSpy spectrum analyzer. I like the idea of using a directional antenna. Looks like some research (may) be underway.
Instead of trilateration you could use bilinear interpolation. This is said to be better for non-linear distance vs. signal strength data like wifi in an urban environment would be. http://courses.cit.cornell.edu/ee476/FinalProjects/s2007/ayl26_ym82/ayl26_ym82/index.htm has the background math and the what I assume is AVR C for doing it with magnetic field sensors.
Using signal strength to judge distance could easily be thrown off by differences in materials blocking line-of-sight to each of the sampling points. It would probably be better to do the sampling with a directional antenna, and from each sampling point, find the bearing that maximizes signal strength to each device you want to locate. With this technique, you can use only two or three sampling locations, depending on the accuracy with which you can estimate the bearings.
Ars Technica has an article about this, citing the Fraunhofer Institute and Skyhooks Wireless. This technology is built into every iPhone and iPad.
Actually I think you should try using an algorithm like the GPS one (wikipedia).. of course you can simplify it according to your need, for example:
you need to install on every item that should broadcast its position (the navigation signal) an application that actually does it
you should use a different channel for every single item to be sure not to generate collisions (it depends also on how much you broadcast the signal)
so if you place at least 4 broadcasters you can triangulate on every client to allow it to calculate its position. Naturally the bcasters should be as much similar as possible in response..
by the way these are just ideas..
I have searched lot of but could not get result or not even know is that result correct or not.
I do have BLE which sends RSSI and TXPower. Actually I am trying to find distance with value of RSSI and and TXPower but can't get correct one. I have followed this and also this as well but don't know which one is correct. What will be the correct formula to get distance from RSSI and TXPower