i need to measure the time between 2 points. I can not use a simple watch because i have no free hands for this. (mountainbike - downhill)
My first idea was to set two GPS points and measure the the time between those points, but I think it will be to inaccurate.
my second idea was to set one bluetooth device to each Point and just measure the distance from me to the bluetooth device , check the shortest distance and save the time.
But than I realized that I would need 3 bluetooth devices to make a distance calculation, which is kinda annoying.
Any idea how i can measure the time between two points with an accuarcy <1sec ?
I want to control this via smartphone.
edit:
Okay i have another idea. Maybe i could set one bluetooth device to each point. I set the signal strenth to <=1m. Than i could easily start and stop the time until i receive the bluetooth signal on my android.
Do you think this would be the best approach ?
It seems you're trying to take total and split times for a course. Definitively, forget of using bluetooth for other things that are not constant transmissions, with slow connection time... (I speak from experience). Of course you want to do it in the cheap, because there already professional solutions for that (e.g.).
From my point of view, if you want something accurate and been able to integrate it with you phone, you'll need the following:
DIY photocell sensors. Maybe involving simple chip (e.g. msp430), phototransistor-diode pair, cheap 433mhz transmitter and batteries.
DIY 433mhz receiver for your phone. There already many boards that supports android open accessory library, (e.g. 49$ from sparkfun), so you only have to connect it to a 433mhz receiver and to your phone.
Custom code programming in your android phone. To be able to receive the signals from the split signal senders and keep track of all times.
It seems to be a pretty decent project for under $250-200(if you self made it :P).
One possible solution that does not require any special hardware would be to use a smartphone at the finish line. You would only need an extra smartphone (SP) with net connection, and some software.
SP sends the start signal to your phone. You start when you hear the signal.
SP uses its camera to detect when you reach the finish line.
SP calculates the time between start and stop and displays it, and possibly sends the info to your phone, too.
Maybe you could even record a video with time stamps.
(Of course, the low cost solution would be to let one of the guys to use a stopwatch at the finish line.)
Related
I am working on a smartwatch project. I want the display to be turned off and only come on when the user brings his hand into the watch-viewing position.
I am running my application on the NRF52 MCU which means machine learning is out of the question. I am using a 3-axis accelerometer from STM.
How can I detect when a user moves his hand into the typically watch viewing position? How is this achieved in smartwatches?
I have the following ideas so far:
- Constantly poll accelerometer and calculate pitch and roll values. Then determine what range of pitch and roll values corresponds to this gesture. This seems a bit wasteful because the CPU will have to be always active.
Is there a simple signal processing algorithm or something similar that can achieve this?
Look into Galvanic skin response sensor - It can measure electrical connectivity of the skin.
When internal or external forces cause arousal — of any kind — the skin becomes a better conductor of electricity. Essentially, when you start to sweat, either from exercise or something else, the band will be able to monitor that.
Detecting when someone is sweating gives the software more information about what a user is doing, which allows for better health tracking. Being able to correlate the level of activity with a different source than just gravity from the accelerometer, allows these programs to take on a more trainer-like role — recommending specific exercises and levels of exertion.
Hope this helps!
What I want to do is to recognize signs on roads using some embedded device with a cam. I was thinking about RaspberryPi 2b, but I don't know if it's power is sufficient. I don't have to analyze every frame of the video, but still the more frames per second I analyze the better especially with high movement speeds.
Question is: Are there any better boards, that could be used for a task like this? (it would be best if they could run Linux/Windows10 on themselves as I am going to use openCV)
for a problem like this you can try to over analyse it and try to pick the hardware before solving the problem. but that is basically the cart before the horse.
first take some video
second digitize it or get it into your daily driver or whatever your preferred software development computer is
start working on the algorithms to solve whatever problem you want to solve, bearing in mind that eventually you want to embed this so you may need to lean more towards lighter weight libraries or roll your own vs heavyweight or operating system dependent solutions (feeding it into photoshop is not a solution, nor is some matlab thing).
you may find that you need better video, important info
eventually you get close to the algorithm and THEN or as you approach the algorithm you can either prototype it on some raspberry pi or beaglebone boards or use a simulator if man hours is cheaper for you that hardware. how many operations per second or per sign or whatever, with some derating how many operations per second do I think i can do on platform X (which is not deterministic, even with experiments as one line of code changed could completely change the performance, esp if on the edge). an instruction set simulator is not going to mimic the pipeline right, but you can take an open source one and modify it to count instructions or types of instructions branches vs non-branches, etc. roughly convert that to clocks, etc. again if hardware is more expensive than man hours. at the price of a raspberry pi and beaglebone black or white it is hard to not just buy one and try it.
a valid stackoverflow question would be, I have this video clip and I am trying to detect whether the car has passed a road sign or not and here is my code but it doesnt work or here is my algorithm but it doesnt work. once past that hurdle another so question could be, I have detected there is a sign in this frame but i cannot detect whether it is a stop sign or yield sign or other, here is my algorithm or code and here are my results and my expected results. another valid so question would be I have this algorithm that works, but I am not able to optimize it for platform X I am close within N percent (needs to be a smallish number less than 20% for example) can this be optimized further.
Hardware For fast Object recognition
You can use Raspberry pi 4 with Google's Usb Accelerator
Partly a coding problem, partly math problem.
Q1. I have an iOS device with compass active. If it knows I'm moving through the field of an iBeacon - or the Beacon is moving through my detection range - would it be possible for a phone to work out (roughly) the relative direction/bearing of that beacon with a series of readings by comparing signal strengths? Has anyone had a try at this?
Q2. Would it be possible to change the Major and Minor values of a beacon regularly (eg: every second) to pass small pieces of info - such as a second user's Bearing and Course?
Q1. It MIGHT be possible but you would need a controlled environment. Either the beacon or the phone needs to be fixed. You also need to be in an area with no obstructions or sources of radio interference.
Then you'd need to use the signal strength (which is sloppy and varies by a fair amount) as one input, and the device's heading info (which is also grossly inaccurate) and do some petty gnarly math on it.
Assuming you could work out the math, the slop in the input readings might make the results too iffy to be useful. (For example, how would you distinguish moving directly towards the beacon from moving 30 degrees to one side or the other? The signal strength would still increase, just not as quickly.
And your algorithm would have to deal with edge cases like moving along a circle around the beacon. In that case the signal strength should not change.
My gut is that even with clever algorithms that input data is just too unreliable to make much sense out of it, beyond "getting warmer" and "getting colder."
As mentioned above, you'd have to track your device's movement within the field, including distance covered and direction, then with multiple readings of signal strength you could theoretically calculate relative direction to the beacon to some degree of accuracy.
As to your second question about changing the minor version number, I have not seen any beacon APIs that allow that, either from the beacon manufacturers or from Apple's implementation.
However, a typical beacon is an ARM or other low power processor with a BLE transceiver, running a program. In theory it should be possible to create your own iBeacon transmitter that changed one of the parameters in order to transmit changing information. You'd have to set up the iOS device with the beacon region only specifying the UUID or UUID and major ID (depending on whether you wanted to change just the minor or change both the major and minor ID in order to transmit changing information.)
Note, too, that iBeacons are a special case of BLE, and the BLE standard does support the sending of arbitrary, changing data. You might be better off implementing your own BLE scheme either instead of or in addition to iBeacons.
I can get the value of Wifi RSSI. but don't know how to convert it into level of Wifi strength as we can see in the menubar in Mac OSX (If I receive a strong Wifi, the wifi status will be bold black on all 4 lines of wifi icon).
Is there any methods or library that I can use to do this? Thx in advance.
I don't think you'll find anything in the API to do this.
I think you might have to Use Science™ and do a manual check, literally walking away from your WiFi access point with laptop in hand, noting down the RSSI values at which the WiFi signal indicator icon changes. Do this a few times and you'll likely find a correlation. I can't imagine it would take more than ten or fifteen minutes to get a good range of sample values.
It's probably worth trying it with more than one type of Mac, if possible.
There is no public API for this. You'll have to figure it out yourself. You might be able to use something simple like (RSSI+100)/8 and then clamp the result between 0 and 4 bars.
Also, you'll want to use a rolling average over a few seconds to keep the bars from jumping around if the signal ends up at a boundary case or jumps around.
PS: AFAIK, Apple uses a more complex algorithm which takes Transmit Rate into consideration.
Good evening all.
I'm just trying to collate some ideas really and was wondering if I could pick some brains.
I'd like to develop an app that relies upon measuring distance reasonably accurately. So for example, I have a central point, I want to be able to detect whether the phone is within a radius of a meter.
How could I achieve this?
The points would be static but I don't think GPS would be accurate enough to rely on this solely.
I'm definitely not a hardware chap but is there a way of combining GPS and some other sort of transmitter to ensure accuracy?
Any help or suggests greatly appreciated.
One meter accuracy? It's probably not going to happen with any phone hardware out there - definitely not with any Windows Phone. GPS isn't accurace enough without a differential beacon, and phones don't have the hardware to receive that (and I doubt you have a differential transmitter either).
The location service on the phone (assuming high accuracy is selected) combines data from GPS, cell towers and WiFi hot spots to provide a location.
There is no way to include the use of other sensors to improve this data.
You also won't be able to get the level of accuracy you're after from the phone. It's just not designed for the purpose you describe.