For an application I need to extend WiFi range where a raspberry pi which is mounted on a drone and is away from station can connect to this WiFi network and stream video.what options are there for me to implement this network?
suppose that the maximum distance between drone(rpi which sends video) and station(router or some thing like that which is connected to a PC and receives video)is 1km.
first of all your project sounds amazing and I would like to see it working on my own eyes :)
And to answer your questions:
1km is quite a distance for all kinds of routers used at home or Access Points hidden inside buildings. Your only hope here is to setup multiple outdoor sector antennas (like THIS beauty from Mikrotik) and CAPsMAN or using Ubiquiti devices with seamless/fast roaming to cover space where drone will fly
With this setup you can easily transfer large streams over large area. Yet the maximal distance will also be affected by number of wireless networks in your vicinity.
Feel free to add more questions. We`ll try our best to help you out
And once done please share some videos, photos, etc with us :)
Related
I'm looking for some advice.
I'm developing a system with geographic triggers, these enable my device to perform certain actions depending on where it is. The triggers are contained within polygons that are stored in my database I've explored multiple options to get this working, however, I'm not very familiar with geo-spacial systems.
An option would be to use the current location of the device and query the DB directly to give me all the polygons that contain that point, thus, all the triggers since they are linked together. A potential problem with this approach, I think, would be the possible amount of polygons stored, and the frequency of the queries, since this system serves multiple devices simultaneously and each one of them polls every few seconds.
An other option I'm exploring is to encode the polygons to an array of geo-hashes and then attach the trigger to each one of them.
Green is the geohashes that the trigger will be attached to, yellow are areas that need to be recalculated with a higher precision. The idea is to encode the polygon in the most efficient way down to X precision.
An other optimization I came up with is to only store the intersection of polygons with roads since these devices are only use in motor vehicles.
Doing this enable the device to work offline performing it's own encoding and lookup, with a potential disadvantage being that the device will have to implement logic to stay up-to-date with triggers added or removed ( potentially every 24 hours )
I'm looking for the most efficient way to implement this given some constrains such as:
Potentially unreliable networks ( the device has LTE connectivity )
Limited processing power, the devices for now are based on a raspberry pi 3 Compute module, however, they perform other tasks such as image processing.
Limited storage, since they store videos and images.
Potential large amount of triggers/polygons
Potential large amount of devices.
Any thoughts are greatly appreciated.
My aim is to count people entering and leaving a bus using overhead camera as shown in the bus and in the mall. How can I do it in Raspberry Pi?
Is there any software or sources or platforms available for it?
A good place to start would be the embedded learning library ELL, available on GitHub.
https://microsoft.github.io/ELL/
I have used it for object classification on a pi with good results. There is a tutorial on using region proposals, which is what you would need to count the multiple object instances. The performance on a pi may or may not be sufficient to catch someone that moves through the door passage quickly, but might serve your purposes.
I've been researching for a while and found tons of helpful resources on this subject, but I figured I would lay down my specifications here so I can get some recommendations from people experienced in this area. It seems like Beaglebone and Raspberry Pi with a Logitech or Microsoft camera are my best options at this point.
My target speed is 50 fps (20 ms per image) with the processing involved. From what I've looked at, this doesn't seem feasible considering most webcams don't go much past 30 fps. More specifically, I need to take the endpoints of an object (like a sheet of paper) and calculate where the midpoint is. Nothing incredibly fancy. 1080p isn't a requirement, I can most likely go much lower. Python is preferable over C and C++ since I've already done a lot of image processing with Python.
It looks like a lot of the code I'll be needing is mostly open-source already, so I really just need to figure out what controller/camera combo I should be using.
It's still a bit of a toss up between the two however here are my views.
The BBB will use a USB web cam and that will take a certain amount of processing power just to get the image. After that you can then manipulate it with SimpleCV
The RPi has a camera board that they say will only use < 3% of the cpu and the rest can be used for processing your image. Plus you can over-clock the RPi to 1Ghz.
Using the RPi with a basic webcam does not give a very good result, whereas the RPi camera works directly on the CSI bus and is set to do 1080 dpi natively. Plus they now have drivers for the camera that work with SimpleCV too.
IMHO I would say that the RPi B and Camera board would be technically faster that the BBB, but it also depends on what manipulation you plan to do :
Marc
Is there a way that I can determine a location of a laptop/phone connected to my router via a wireless network access point? (I do not want to use GPS... only the access point).
No. But let's examine why.
If you can get the metrics from the router, which might or might not be possible, you can get the signal strength. This will give you a circle. But, this is limited, as you also need to know how strong the WiFi card is to determine rough distance. But, you probably know the rough distance your router works under, or the max circle, so this is not very useful.
If you have more than one access point, however, you can use triangulation. With two, the information is limited; three or more will give you a more accurate distance and allow you to extrapolate the strength of the signal.
Nope. You might be able to estimate its distance away, but even that is not likely if you're inside a building. Various building materials attenuate the signal, so the response is non-linear. If your router has two separate antennas, and you can measure the signal strengh from each independently, then you might have a chance of getting a feel for the direction, but I doubt the signal resolution will be high enough to give you any meaningful data.
Yes. However you'll need more than one Access Point and some serious software.
There are a number of solutions available and in-development for Location Based Services in Wi-Fi Networks. As Gregory mentioned above a single AP is not enough to do anything but poor range estimation, however multiple APs do not typically use triangulation to determine the location solution, they use a trained Hidden Markov Model.
A general question: is it possible to retrieve information about how far away e.g. a computer is from a wifi-router. For instance I want to get data on my computer if I'm 10 meters away from my home-wifispot or 2 meters.
Any idea if that is even possible?
Edit: How about bluetooth? Is it possible to get information about how far away bluetooth-connected devices are one from another?
I would recommend a measuring line or just good-old-fashioned guesstimating.
There is no "simple" way to do it (complex ways may involve building "accurate" signal maps ahead of time or trying to fit a better equation which is still subject to anumber of the limitations with the naive rule) and the rule of thumb "1/r^2" is just that -- a general rule of thumb. On the other hand, perhaps there is some existing software that will show you your RSS strength and make the task feel accomplished :-)
You will find useful links if you google for "RSS signal distance". This kind of task seems quite a common topic in academia w.r.t. small wireless devices ("motes") as well and there have been some interesting approaches to this problem such as the fitting of secondary low-frequency acoustic sensors.
You can query the signal strength which is some kind of indication of distance and obstructions and a few other factors all rolled into one measure. With just plain wifi though this isn't possible directly.
Try measuring the response time of the router to pings, with the data rate set to constant to avoid that effecting the response time. Take lots of samples and remove outliers to reduce errors, but you will still have a substantial quantization error. Subtract the latency of the router and computer, divide by 6 then multiply by the speed of light and hopefully you will have the distance to a resolution of a few metres.