I'm trying to find the distance between two bluetooth beacons which are typically in the distance of 60cm or less. Direction is not an issue, I'm only looking to figure out the distance between the beacons and there will be no interferences such as walls/objects in between. Is it possible to detect the distance through RSSI Measurements? and if so what will be the expected accuracy?
122944
I currently have a setup where I send a char using a Tx of 434MHz and an Uno to a Mega with a Rx. The Mega counts how many times it receives the char and then if it falls below a certain number it triggers an alarm. Is this a viable way to measure the distance between two microcontrollers while indoors or is there a better way.  Transmitter (Mega)  #include &lt;SoftwareSerial.h&gt;  int rxPin=2; //Goes to the Receiver Pin int txPin=5; //Make sure it is set to pin 5 going to input of receiver  SoftwareSerial txSerial = SoftwareSerial(rxPin, txPin); SoftwareSerial rxSerial = SoftwareSerial(txPin, rxPin); char sendChar ='H';  void setup() {   pinMode(rxPin, INPUT);   pinMode(txPin,OUTPUT);   txSerial.begin(2400);   rxSerial.begin(2400); }  void loop() {   txSerial.println(sendChar);   Serial.print(sendChar); }   Receiver  #include &lt;SoftwareSerial.h&gt;  //Make sure it is set to pin 5 going to the data input of the transmitter int rxPin=5;  int txPin=3; //Don't need to make connections int LED=13; int BUZZ=9; int t=0;  char incomingChar = 0; int counter = 0;  SoftwareSerial rxSerial = SoftwareSerial(rxPin, txPin);  void setup() {   pinMode(rxPin, INPUT); //initilize rxpin as input   pinMode(BUZZ, OUTPUT); //initilize buzz for output   pinMode(LED, OUTPUT); //initilize led for output   rxSerial.begin(2400); //set baud rate for transmission   Serial.begin(2400); //see above }  void loop() {   for(int i=0; i&lt;200; i++) {     incomingChar = rxSerial.read(); //read incoming msg from tx      if (incomingChar =='H') {       counter++; //if we get bit "h" count it       }     delay(5); //delay of 10 secs   }   Serial.println(incomingChar);   Serial.println(counter); //prints the the bits we recieved    if(counter&lt;55) {     //if we receive less than 100 bits than print out of range triggers alarm     Serial.println("out of range");      tone(BUZZ,5000,500);digitalWrite(LED,HIGH);   }   else {     noTone(BUZZ);digitalWrite(LED, LOW);     //if we get more than 100 bits than we are within range turn off alarm     Serial.println("in range");    }    counter = 0;   incomingChar=0; }
45328
I am trying to detect a signal when a headphone is connected or disconnected from the system.  What is the best way to do this?  If there is a special board with drivers, that will be my preferred way.
13486
I've been trying to pair up my bluetooth keyboard with my computer after reinstalling from a standard ubuntu 12.04 to a minimal install.  In the minimal install I have no gui, so I've been trying to use the various command line tools available, but I can't figure out how the pairing is supposed to go. Pairing when I had a gui worked flawlessly.  I've asked for help here:   No one has replied but a lot of details of my situation is available there.  How is one supposed to pair bluetooth devices from the command line?
80560
Why does the apparent size of an object change when it is farther away from me compared to when it is closer to me?  Can someone perhaps explain this through an optics perspective?
48219
The function  should calculate distances between two points.  When I am trying to calculate distance between points having 100 meters between them  p1=new esri.geometry.Point(3997030.6690969253, 7444299.320646087, new esri.SpatialReference({ wkid: 102113 })); Object p2=new esri.geometry.Point(3996951.455397143, 7444142.154020177, new esri.SpatialReference({ wkid: 102113 })); Object esri.geometry.getLength(p1, p2) 176.00045037719127   I am getting 176 which is wrong. Projection is Web Mercator (WKID 102113).    @Krystian found that getLength uses just Pythagoras theorem to calculate length. So it gives length in projection meters. How to obtain distance in real meters?
41973
Every day you walk from point A to point B, which are $3$ miles apart. There is a $50$% chance each walk that there is an invisible wall somewhere strictly between the two points (never at A or B). The wall extends $1$ mile in each direction perpendicular to the line segment (direct path) between A and B, and its position can be at any random location between the two points. That is, it can be any distance between A and B such as $0.1$ miles away from A, $1.5$ miles away, $2.9$ miles away.... You don't know if the wall is present or where it is until you walk into it.  You must walk around the wall if present as there is no other way to circumvent it.  Assume the wall is negligible thickness (like a force field), all ground is perfectly flat, and the y coordinates at both A and B are $0$ (although I don't think the optimal path will change much if they weren't).  What strategy minimizes the average expected walk distance between A and B?  How do we know for certain this strategy yields the shortest average walking distance?  To get the $100$ bounty points, I would like a convincing argument from you as to why you feel your solution is optimal and cannot be beaten.  For those of you using computer simulation, anything reasonably close to optimal is a candidate for the bounty.   Can anyone beat the optimal solutions submitted so far?  There are still a few days to try.  Even a slight beat (if not due to roundoff error or some other error) would help prove previous solutions are non-optimal.  You can just use the table of $31$ points (x-y coordinates) and compute that path length and then if you can find better then I will accept that answer.  I think by Sunday night I may have to award the bounty otherwise it may get auto-awarded.
120323
I am currently writing some code to do multilateration using TDOA and currently struggling and wondering if anyone has any reference code that can be used as a test case with some sample data that I have!  At the moment I am unsure if it is the code I have written or whether it is the geometry of the points that is off.  One example group of packets that I have received is  station1 = [50.919149572907784,-1.005043823556842,90.729]; station2 = [50.8304,-1.21956,0]; station3 = [51.0569,-1.26224,100];  stations = [station2,station1,station3]; timestamps = [28704.175275109, 28704.175334203, 28704.175334875];   My code currently locates this to 50.910447339754654,-1.2347406519401736 which I am 99% sure is wrong!  Does anyone have any code that can verify this at all?  One bit of code I am testing against and get very similar results is
64803
At 10:30 am car $A$ starts from point $A$ towards point $B$ at the speed of $65$ km/hr, at the same time another car left from point $B$ towards point $A$ at the speed of $70$ km/hr, the total distance between two points is $810$ km, at what time does these two cars meet ?  This is what I have tried,     $t_1 = \frac{810}{65} \,$ km/hr $= 12.46 \, $hr    $t_2 = \frac{810}{70} \,$ km/hr $= 11.57\,$ hr     $t_1-t_2 = 0.89 \,$ hr    $t_1-t_2 = 0.89\cdot 60 = 53.4 \,$ minutes   but this couldn't be the answer because how could these two cars could meet after $53.4$ minutes ?
103842
Given that space is not a perfect vacuum, what is the speed of sound therein? Google was not very helpful in this regard, as the only answer I found was $300\,{\rm km}\,{\rm s}^{-1}$, from , which is not a source I'd be willing to cite.
116158
I'm looking for the appropriate theoretical framework or speciality to help me deal with understanding how to deal with the errors that the GPS system has - especially when dealing with routes.  Fundamentally, I'm looking for the requirements on the data and any algorithms to use to be able to establish the length of a trail. The answer needs to be trustworthy.  A friend of mine was the race director of a race which was billed as 160km but the Garmin watches everybody has makes it more like 190km+. It caused quite some grief at the finish line, let me tell you!  So my friend went back to the course with various GPS devices in order to remap it and the results are interesting.  Using a handheld Garmin Oregon 300 she got 33.7km for one leg. For the same leg on a wrist watch Garmin Forerunner 310xt it came out to 38.3km.  When I got the data from the Oregon it was obvious that it was only recording data every 90 seconds or so. The Forerunner does it every couple of seconds.  When I plotted the data from the Oregon I could see that it got confused by some switchbacks and put a line straight through them and a curve was made a little less.  However, I muse that the difference in the recording frequency is much of the explanation. i.e. by recording every couple of seconds the Forerunner is closer to the real route. However, there will be an amount of error because of the way GPS works. If the points recorded are spread around the real route randomly (because of the error) then the total distance will be larger than the real route. (A wiggle line going either side of a straight line is longer than the straight line).  So, my questions: 1. Are there any techniques I can use on a single dataset to reduce the error in a valid way? 2. Does my theory about the difference in recording frequency hold water? 3. If I have multiple recordings of the same routes are there any valid techniques to combine them to get closer to the real route?  As I say, I don't really know what to search for to find any useful science about this. I'm looking for ways to establish just how long a given piece of trail is and it is very important to people. An extra 30km in a race is an extra 5+ hours we weren't expecting.  As requested here is some sample data:       Thanks for any advice you can give.
4745
When I use a compass it does not seem to point towards my bed. I have heard that now compasses point towards North. Is this true?
35891
I am using a proximity sensor on a battery powered wearable sensor and maybe facing some detection issues because of a bad grounding. I am seeing detection differences between the sensor system powered through USB (which I undestand,) the battery powered sensor in a hand, and the battery powered sensor on a desk. I have spent a lot of time searching about that topic but I didn't really find answers to fully understand. Do you have links/documents to explanations giving equations, drawings and numerical examples? Additionally:  I have seen that self-capacitance is really dependant on good grounding (system to ground only, as human body to ground is generally high enough to not be considered) but that for mutual-capacitance, the sensor sensitivity is not, and really low impacted by it. Why is that? Is it the reason why smartphones or other commercialized capacitive sensors are so performant, or is it due to hardware specifity or even different algorithm used?  EDIT: 10/11/2020 14h33 I am using a microchip MTCH101 IC as a proximity detector. I know this is not exactly the same technology, as proximity detector is based on a self-capacitance, increasing the range of detection but with maybe some unwanted coupling, and capacive screen are mainly using mutual-capacitance technology, increasing precision thanks to a radiated field vertically lower and more directionnal which avoids unwanted coupling with others adjacent sensors. Is this the mutual-capacitance architecture or the algorithm behind that makes smartphone more robust to grounding issue ? or the Hardware architecture maybe? I have read many times that mutual-capacitance is less dependant from grounding issue than self-capacitance, is it true? why ? (but never seen equation to prove it) ? Is any fundamental detecting methods (CTMU, CVD, CSM,...) better than an other for grounding issue? For self-capacitance, the grounding issue is comming from the fact the wearable battery power supplied device has a unfix and sometime low capacitance between its local ground and the earth. There is 2 cases: when it's handled by the second hand of the user and when the device is laid on a table. When there is a good coupling (high capacitance), its negligible and only the sensing electrode is measured. When it's not, the ground to earth coupling is taking part to the measurement as parasitic. I have found that the following way would help to improve this coupling : Big ground plane at the device back, to increase surface which will be seen by the second hand or the table. connexion from the device local ground to the device casing to let the human hand which hold the device have a contact with local ground and a better coupling. Heating pipe (which i do not know) &quot;Use human finger to modify an electrical field between the electrode and the system ground, working as a dielectric constant modified&quot;. I interpret that as mutual-capacitance, is that correct ? Finally, why the mutual capacitance would have less that kind of issue since that the charge exchanged with the finger are still flowing throught the earth and the device ground ?
92500
I am not a physicist but I am extremely interested in this area.  The simple version of my question is:  "What is the maximum range of an ultrasonic wave traveling through air?" Now, I know it depends on the exact frequency, air temperature, humidity, ... I don't need to know exact number. I just need to know the order of magnitude. Is it ~1m? ~10m? ~1000m?  I also know that this range is finite due to wave's attenuation and attenuation is higher as frequency is higher. So this question could possibly be translated into these two: "What is the minimum ultrasonic wave amplitude detectable by a commercially available sensor?" + "What is the maximum ultrasonic wave amplitude that can be emitted by commercially available ultrasound emitter?"
24198
The currently proposed Gravitational wave detection apparatus consists of Michelson Interferometer which is supposed to measure distances of the order of $10^{-22}$m. But the wavelength of the light used is in the order of micrometers ($10^{-6}$m). How is this possible? The conventional way to measure distance is by counting the interference fringes. But for path difference smaller than wavelength of laser light this is not possible.
17716
The theorem 1 is the result in Emil Bjornson's paper (PILOT-BASED BAYESIAN CHANNEL NORM ESTIMATION IN RAYLEIGH FADING MULTI-ANTENNA SYSTEMS).  I want to know the proof omitted. Please, help me.
24440
What is the expected minimum euclidean distance between $N$ points uniformly and independently chosen on the shell(sphere) of 3-D ball of radius $R$?   Note that the expected minimum distance might be difficult to compute, so a good lower bound is also fine.   My approach  I take the approach similar to this   .   Suppose we put $N$ circles of radius $r$ uniformly on the surface of the ball. Therefore we could compute the expected minimum distance by the following expression \begin{align} E[D]=\int_0^\infty P(D&gt;t) dt. \end{align}  So, it remains to compute  $P(D&gt;t)$. Actually, since we are after a lower bound on  $E[D]$ it is enought to give a lower bound on $P(D&gt;t)$.  Let $S_i$ be the event that the pair of circles does not intersect which should be given by \begin{align} P(S_i) =  \frac{ Surf(R)-Surf(r)}{Surf(R)}= 1-\frac{  \pi r^2}{ 4\pi R^2}=1-\frac{ r^2}{ 4 R^2} \end{align}  Now the probability that euclidean minimum distance $D$ between $N$ balls is bigger than $t$ should be similar to  \begin{align} P[ D \ge t] \stackrel{?}{=}  P[ \cap S_i] \end{align} However, I think we somehow need to converte from the geodesic distance to euclidean distance but I am not very sure how to do that?
50082
Me and my sibling want to play Minecraft together. Is there a way to use Bluetooth instead of WiFi to get connected? If so, how? We have MCPE version 15.0.