Is there any way to achieve users current location using satellite without GPS(Internet) and without SIM Network.
GPS does not require internet, it requires a gps chip and a processing chip.
The GPS is multiple satellites (what you are asking for) that transmit signals to the ground, these satellite orbit the earth in the LEO (low earth orbit) and there are enough of them to cover the whole globe.
We need internet to fetch the map tiles, street names, traffic and navigation utilities, not the user location.
So using the signal we get from these satellites can be processed into the location of the user with accuracy depending on how many satellites you are listening to (minimum of 3).
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I am currently making an indoor localization system using Bluetooth RSSI. The device that I want to track is a transmitter and there are many receivers placed in fixed positions inside the room. Based on the RSSI, I can roughly get the distance. And of course the farther the device is, the worst accuracy I get. I succeed in calculating the x and y for the transmitter using trilateration, but because of the noisy signals, the position is jumping around. What is the best way of filtering / averaging so that the position don't jump around?
As part of a course on my university we've been given the task of taking the live wind telemetry from a drone and then feeding it to a neural network so that it gives better estimates than just using a sensor.
The research we've concluded so far tells us that our drone, the DJI Mavic 2 Zoom, is only compatible with the Windows SDK but not the onboard SDK.
Simply our question is; is there any way for us to send the raw wind speed and direction data from the drones sensors to a computer?
Create Android application with DJI Mobile SDK and send data from msdk to your computer with wifi.
The SDK only provides the wind warning level(0, 1 and 2). It does not provide any information regarding the direction from which the wind is blowing or the actual speed of the wind.
The aircraft tries to stay in it's current position on it's own, even if there is moderate wind blowing. However the drone does not tell the user how much it has to work in which direction to negate the effect of the wind.
I assume you're better off with accessing real time wind information for your position from a weather service on the internet, if that's available in your country.
I've done a wind meter app.
The best method is:
Fly against the wind
In virtualstick use angle mode, and set pitch and roll to 0 This will let the drone drift with the wind.
Slowly rotate the yaw.
Meassure the speed, when it stop increasing, the gps-speed gives you the windspeed and direction.
Warning, in strong wind you have to fly for quite a while against the wind.
The yaw rotation needs to be done due to the drone is never exactly leveled, and it will pick up speed at one direction. If turned, it cancel that out.
Send the info to a server over internet/wifi.
I've done this on an android phone connected the controller.
Windows api doesn't seem to support virtualsticks, which I find strange. In that case it must be done on android or ios, and trasnmitted to a server. I might be wrong since I never used the windows api.
I am planning to create the indoor navigation system. It will provide the shortest path to user from source to destination.
Suppose I know all beacons location.
Is that possible to calculate user facing direction by a set of beacons?
Sorry, this is not possible.
Off the shelf beacons are omnidirectional transmitters and mobile phones are omnidirectional receivers. There is no way to determine directionality of the signal.
The good news is that phones have two other ways of getting heading information -- the compass and a velocity vector. The compass is the general approach if you are standing still. If you are in motion, just calculate a vector between the last known location and the current location to get the heading.
I am planning on a robot, basically an Arduino coupled with a webcam and RC car to navigate from a point in the house to another using a map of the house layout made possibly by a webcam tour of the place.
It should receive a command to where it should go based on input from my smartphone or PC. Each room will have an ID code which the robot should use to determine the travel path.
Also, it should be able to go to the room where I am based on locating me using Bluetooth or Wifi.
Sensors: Proximity sensors and light sensors
I live in the house, so that is not an issue.
Any ideas on where I can start?
I participated in a similar project, it will be more difficult than you think now.
We used bluetooth beacons. Fix their positions, then you can measure the signal strength with the robot. If you know the positions of the beacon (they are fix), then you can calculate where is the robot actually. But they are very inaccurate, and takes a couple of seconds to scan all the beacons.
If you want to navigate through your house, I think the easiest way that you plant the beacons, go around in the house with the robot and measure the signals (the more the better). This way you can create a discrete layout of your house. In my opinion the easiest way to store the map if you represent the layout as a graph. The nodes are the discrete points you measured, and there exists an edge between two nodes if the robot can travel between them in "one step". This way you can represent temporary obstacles too, for example delete an edge. And the robot can easily determine which way to go, just use Dijsktra's algorithm.
Is there anyway to disable the "inertial motion sensors" for a program, so that my program does not track the devices acceleration? I've noticed that if a user suddenly moves and then suddenly stops with the device the motion tracking becomes inaccurate.
Even if you could, "disabling the sensors" is not a good idea. And when you say "disabling" I assume you mean setting them to an initialization state rather than just ignoring the data stream. The 3-axis accelerometer and gyroscope data are fused with position data to provide your relative location during motion tracking. You have no way of knowing which of these data streams is the source of the inaccuracy, and just turning off acceleration would likely require a re-calibration of all sensors so that tracking (data fusion) is accurate.
Replicate the error with as much data as possible (speed, stopping time, orientation of the tablet, distance to the nearest object, nearest object characteristics, etc.) and report it to the project Tango team.