I have a IoT system in home and two temperature sensors.
One of the sensors could work in some hours in direct sun.
The real temperature is always the lowest value, so sometimes temp1, sometimes temp2.
What I want to achieve is:
read the temperature from sensors1 (via MQTT)
read the temperature from sensors2 (via MQTT)
compare values
find the lowest one and send in via MQTT
go back to reading in loop
For this example I can simulate readings with injection nodes
How to do that? I am new in Node-Red, have tried but without success.
Here is my flow:
[{"id":"fa6372cc.47f92","type":"tab","label":"Flow 8","disabled":false,"info":""},{"id":"5ac90e03.22da3","type":"join","z":"fa6372cc.47f92","name":"","mode":"custom","build":"object","property":"payload","propertyType":"msg","key":"topic","joiner":"","joinerType":"str","accumulate":true,"timeout":"","count":"2","reduceRight":false,"reduceExp":"","reduceInit":"","reduceInitType":"","reduceFixup":"","x":990,"y":340,"wires":[["f09774bf.3c8428","a197b84d.6a7338"]]},{"id":"f09774bf.3c8428","type":"debug","z":"fa6372cc.47f92","name":"","active":true,"tosidebar":true,"console":false,"tostatus":false,"complete":"true","x":1130,"y":340,"wires":[]},{"id":"43900e79.98cd8","type":"change","z":"fa6372cc.47f92","name":"set payload value","rules":[{"t":"set","p":"payload","pt":"msg","to":"req.params.value","tot":"msg"}],"action":"","property":"","from":"","to":"","reg":false,"x":790,"y":340,"wires":[["5ac90e03.22da3"]]},{"id":"b71d9143.c03bd","type":"change","z":"fa6372cc.47f92","name":"set topic temp1","rules":[{"t":"set","p":"topic","pt":"msg","to":"temp1","tot":"str"}],"action":"","property":"","from":"","to":"","reg":false,"x":560,"y":320,"wires":[["43900e79.98cd8"]]},{"id":"e87114aa.6cd1","type":"change","z":"fa6372cc.47f92","name":"set topic temp2","rules":[{"t":"set","p":"topic","pt":"msg","to":"temp2","tot":"str"}],"action":"","property":"","from":"","to":"","reg":false,"x":560,"y":360,"wires":[["43900e79.98cd8"]]},{"id":"783c47fd.8dd58","type":"inject","z":"fa6372cc.47f92","name":"temp source 2","topic":"","payload":"12","payloadType":"num","repeat":"3","crontab":"","once":false,"onceDelay":"1.5","x":380,"y":360,"wires":[["e87114aa.6cd1"]]},{"id":"271dedab.aaa7b2","type":"inject","z":"fa6372cc.47f92","name":"temp source 1","topic":"","payload":"10","payloadType":"num","repeat":"2","crontab":"","once":false,"onceDelay":"1","x":380,"y":320,"wires":[["b71d9143.c03bd"]]},{"id":"a197b84d.6a7338","type":"mqtt out","z":"fa6372cc.47f92","name":"temperature","topic":"domoticz/in","qos":"","retain":"","broker":"7e3561ec.acad","x":1150,"y":280,"wires":[]},{"id":"7e3561ec.acad","type":"mqtt-broker","z":"","name":"Domoticz","broker":"192.168.6.11","port":"8084","clientid":"","usetls":false,"compatmode":true,"keepalive":"60","cleansession":true,"birthTopic":"","birthQos":"0","birthRetain":"false","birthPayload":"","closeTopic":"","closeRetain":"false","closePayload":"","willTopic":"","willQos":"0","willRetain":"false","willPayload":""}]
One way to do it would be like this:
This is storing the two temps in flow variables - the first flow initially sets them to a high number so the "min" in "choose lower value" will later work. In this case I've used a change node setting the payload to the JSONata of
$min([$flowContext("temp1"), $flowContext("temp2")])
but there's a few ways you could choose to do it.
Here is the code to try:
[{"id":"6bc2755e.9feb9c","type":"debug","z":"f454a93f.0e89d8","name":"","active":true,"tosidebar":true,"console":false,"tostatus":false,"complete":"true","x":990,"y":340,"wires":[]},{"id":"38bd03eb.f7d06c","type":"change","z":"f454a93f.0e89d8","name":"choose lower value","rules":[{"t":"set","p":"payload","pt":"msg","to":"$min([$flowContext(\"temp1\"), $flowContext(\"temp2\")])\t","tot":"jsonata"}],"action":"","property":"","from":"","to":"","reg":false,"x":790,"y":340,"wires":[["6bc2755e.9feb9c"]]},{"id":"9066677f.eb0358","type":"change","z":"f454a93f.0e89d8","name":"store temp1","rules":[{"t":"set","p":"temp1","pt":"flow","to":"payload","tot":"msg"}],"action":"","property":"","from":"","to":"","reg":false,"x":550,"y":320,"wires":[["38bd03eb.f7d06c"]]},{"id":"a70c9b2a.e7db58","type":"change","z":"f454a93f.0e89d8","name":"store temp2","rules":[{"t":"set","p":"temp2","pt":"flow","to":"payload","tot":"msg"}],"action":"","property":"","from":"","to":"","reg":false,"x":550,"y":360,"wires":[["38bd03eb.f7d06c"]]},{"id":"4bd27616.d022c8","type":"inject","z":"f454a93f.0e89d8","name":"temp source 2","topic":"","payload":"12","payloadType":"num","repeat":"","crontab":"","once":false,"onceDelay":"1.5","x":370,"y":360,"wires":[["a70c9b2a.e7db58"]]},{"id":"7378dd4f.3825b4","type":"inject","z":"f454a93f.0e89d8","name":"temp source 1","topic":"","payload":"10","payloadType":"num","repeat":"","crontab":"","once":false,"onceDelay":"1","x":370,"y":320,"wires":[["9066677f.eb0358"]]},{"id":"314eb0ec.85211","type":"inject","z":"f454a93f.0e89d8","name":"","topic":"","payload":"","payloadType":"date","repeat":"","crontab":"","once":true,"onceDelay":0.1,"x":370,"y":260,"wires":[["688646b.138a6b8"]]},{"id":"688646b.138a6b8","type":"change","z":"f454a93f.0e89d8","name":"set to high","rules":[{"t":"set","p":"temp1","pt":"flow","to":"999","tot":"num"},{"t":"set","p":"temp2","pt":"flow","to":"999","tot":"num"}],"action":"","property":"","from":"","to":"","reg":false,"x":550,"y":260,"wires":[[]]}]
I'm trying to demodulate a signal using GNU Radio Companion. The signal is FSK (Frequency-shift keying), with mark and space frequencies at 1200 and 2200 Hz, respectively.
The data in the signal text data generated by a device called GeoStamp Audio. The device generates audio of GPS data fed into it in real time, and it can also decode that audio. I have the decoded text version of the audio for reference.
I have set up a flow graph in GNU Radio (see below), and it runs without error, but with all the variations I've tried, I still can't get the data.
The output of the flow graph should be binary (1s and 0s) that I can later convert to normal text, right?
Is it correct to feed in a wav audio file the way I am?
How can I recover the data from the demodulated signal -- am I missing something in my flow graph?
This is a FFT plot of the wav audio file before demodulation:
This is the result of the scope sink after demodulation (maybe looks promising?):
UPDATE (August 2, 2016): I'm still working on this problem (occasionally), and unfortunately still cannot retrieve the data. The result is a promising-looking string of 1's and 0's, but nothing intelligible.
If anyone has suggestions for figuring out the settings on the Polyphase Clock Sync or Clock Recovery MM blocks, or the gain on the Quad Demod block, I would greatly appreciate it.
Here is one version of an updated flow graph based on Marcus's answer (also trying other versions with polyphase clock recovery):
However, I'm still unable to recover data that makes any sense. The result is a long string of 1's and 0's, but not the right ones. I've tried tweaking nearly all the settings in all the blocks. I thought maybe the clock recovery was off, but I've tried a wide range of values with no improvement.
So, at first sight, my approach here would look something like:
What happens here is that we take the input, shift it in frequency domain so that mark and space are at +-500 Hz, and then use quadrature demod.
"Logically", we can then just make a "sign decision". I'll share the configuration of the Xlating FIR here:
Notice that the signal is first shifted so that the center frequency (middle between 2200 and 1200 Hz) ends up at 0Hz, and then filtered by a low pass (gain = 1.0, Stopband starts at 1 kHz, Passband ends at 1 kHz - 400 Hz = 600 Hz). At this point, the actual bandwidth that's still present in the signal is much lower than the sample rate, so you might also just downsample without losses (set decimation to something higher, e.g. 16), but for the sake of analysis, we won't do that.
The time sink should now show better values. Have a look at the edges; they are probably not extremely steep. For clock sync I'd hence recommend to just go and try the polyphase clock recovery instead of Müller & Mueller; chosing about any "somewhat round" pulse shape could work.
For fun and giggles, I clicked together a quick demo demod (GRC here):
which shows:
I have a bunch of questions concerning Timing Advance in GSM :
When is it defined ?
Is it the phone or the BTS who's in charge of defining it's value ?
is it dynamic, does it depends on certain situations ?
Let's say that I figured out a way to get the exact value of the Timing Advance (GSM Layer 1 Transmission level) from the phone's modem :
In order to verify my solution, I'm supposed to put my phone over and over in a situation where he have to use/change the Timing Advance while I log its value...
How can I do that ?
Thanks
In the GSM cellular mobile phone standard, timing advance value corresponds to the length of time a signal takes to reach the base station from a mobile phone. GSM uses TDMA technology in the radio interface to share a single frequency between several users, assigning sequential timeslots to the individual users sharing a frequency. Each user transmits periodically for less than one-eighth of the time within one of the eight timeslots. Since the users are at various distances from the base station and radio waves travel at the finite speed of light, the precise arrival-time within the slot can be used by the base station to determine the distance to the mobile phone. The time at which the phone is allowed to transmit a burst of traffic within a timeslot must be adjusted accordingly to prevent collisions with adjacent users. Timing Advance (TA) is the variable controlling this adjustment.
Technical Specifications 3GPP TS 05.10[1] and TS 45.010[2] describe the TA value adjustment procedures. The TA value is normally between 0 and 63, with each step representing an advance of one bit period (approximately 3.69 microseconds). With radio waves travelling at about 300,000,000 metres per second (that is 300 metres per microsecond), one TA step then represents a change in round-trip distance (twice the propagation range) of about 1,100 metres. This means that the TA value changes for each 550-metre change in the range between a mobile and the base station. This limit of 63 × 550 metres is the maximum 35 kilometres that a device can be from a base station and is the upper bound on cell placement distance.
A continually adjusted TA value avoids interference to and from other users in adjacent timeslots, thereby minimizing data loss and maintaining Mobile QoS (call quality-of-service).
Timing Advance is significant for privacy and communications security, as its combination with other variables can allow GSM localization to find the device's position and tracking the mobile phone user. TA is also used to adjust transmission power in Space-division multiple access systems.
This limited the original range of a GSM cell site to 35km as mandated by the duration of the standard timeslots defined in the GSM specification. The maximum distance is given by the maximum time that the signal from the mobile/BTS needs to reach the receiver of the mobile/BTS on time to be successfully heard. At the air interface the delay between the transmission of the downlink (BTS) and the uplink (mobile) has an offset of 3 timeslots. Until now the mobile station has used a timing advance to compensate for the propagation delay as the distance to the BTS changes. The timing advance values are coded by 6 bits, which gives the theoretical maximum BTS/mobile separation as 35km.
By implementing the Extended Range feature, the BTS is able to receive the uplink signal in two adjacent timeslots instead of one. When the mobile station reaches its maximum timing advance, i.e. maximum range, the BTS expands its hearing window with an internal timing advance that gives the necessary time for the mobile to be heard by the BTS even from the extended distance. This extra advance is the duration of a single timeslot, a 156 bit period. This gives roughly 120 km range for a cell.[3] and is implemented in sparsely populated areas and to reach islands for example.
Hope this Answer the question:)
It's defined everytime the BTS needs to set the define the phone's transmission power, which happens quite often.
It's the core system (BTS in GSM) who totally in charge of defining it's value.
It's very dynamic, and change a lot. Globally, the GSM core system is constantly trying to find the exact distance between the BTS and the MS, so it constantly make a kind of "ping" to calculate it. The result of such operations is generally not that accurate since there are a lot of obstacles between the mobile and the BTS (it's not a direct link in an open space).
Such operations happens a lot, so use your smartphone. Simply.
I want to build a Javascript/HTML5 geolocation based social network and I wonder the best choice of possible architectures. Client-server can be simple to develop but drawback is the system ressources that could be very high, especially because the application must manage moves (worst case: a user that is in a car must see others users that are around him in cars).
Basicaly, in a client-server architecture, server tasks will be :
collects and stores latitude and longitude of the users (could have thousands of them)
makes geo distance search for that user (to get the list of users present around him in a radius)
builds and sends to the client an XML file with position of the users in the list
These 3 operation must be done periodically, every 3 or 5 seconds because I want a "live" map that shows users in the list moving in their environnement (city, town).
All these 3 points could be optimized :
client send his position when moving of 10 meters to reduce amount of data to process
"spherical rectangle" search in MyISAM table with spatial index (use of MBRContains) to off load MySQL database.
common output file : the XML that is sent can be the same if 2 users are located in a radius of x meters (the 2 users are close each-other).
It is hard to make load estimation at this stage but I think client-server architecture is not appropriate for that type of application and peer2peer could be a nice answer if 2 clients could communicate when they are near each other.
My point is:
Is there any methode to make possible a client to blind search other clients that are located in a certain radius without the help of a central server ? (it is possible with UDP broadcast :-)
edit : Correction. UDP Brodcast allow a client to poll a machine wherever it is, in certain range or IP address.
Thank you for your help,
Florent
You will have to have central peers/servers, because you need to centralize some information to be able to perform you functionalities.
I would go for the following:
Assign square miles (or whatever size you want) to specific servers.
Have devices send a 'I am here' message with their coordinates to some dispatcher that will forward these to the correct square mile server for handling.
Have servers register when a device enters a square mile they manage. This could be a central map to make sure a device is registered to one and only one square.
Forward this message to all other devices in the square.
And/or make sure you include to which square this message is intended and make sure the devices checks it before displays it to the user.
Tune the size of the square and the rate of 'I am here' message. That's it.
The answer actually depends on many things so I'll help out with basic strategy. To understand things out you'll need to understand how does Kademlia works (Kademlia is a DHT P2P network that stores information).
In Kademlia at first startup each node picks random ID which is a 160 bit number that represents point in a space of all possible 160 bit IDs.
The ID of the information that needs to be stored is obtained with SHA-1 function (it receives arbitrary string, and outputs 160 bit number that is treated like ID of the information that needs to be stored)
After that you have the ID of the information, you publish it, the information is physically stored on a node that has it's ID close to information ID.
(The illustration is taken from here)
The information is queried via it's ID. Both the information lookups or node lookups takes O(log(N)) hops to obtain the required information. The "XOR" metric is used in Kademlia (in your case it can be ordinary Euclidian metric).
Each node maintains an array of buckets, each bucket contains addresses of nodes that are appropriate to the current bucket. The appropriate'ness is a measure of how close the IDs are. consider example:
0 160
Node 1 ID: 1101000101011111101110101001010...
Node 2 ID: 1101011101011111101110101001010...
Node 3 ID: 1101000101011001101110101001010...
After applying XOR metric to Nodes #1,2 i.e (computing the number that represents the virtual distance between these nodes) we get:
index - 012345678901234
xor - 000001100000000... (the difference is in 5-th msb bit)
order - msb lsb
After applying Xor metric to Nodes #1,3 we get:
index - 012345678901234
xor - 000000000000011... (the difference is in 13-th msb bit)
order - msb lsb
Apparently Node 1 is closer to Node 3 since it has difference in less significant bits than the distance from Node 1 to Node 2. And therefore from a point of view of a Node 1, it's neighbor Node 3 goes to 13-th bucket(higher index means closer IDs), and Node 2 goes to to 5-th bucket which contains a group of nodes that are 5 MSB radixes away from a current node ID.
Such data structure allows each node to know it's surroundings in variety of 160 levels of distances.
Back to your example, to allow efficient geospacial queries you'll need to replace Kademlias XOR metric with ordinary Euclidian metric. In this case you will have your ID's as a 3D or 2D vectors, and unfortunately due to fact that Euclidian metric results with floating point numbers which are not directly suitable for this type of algorithm so you will need to convert them to a discrete binary numbers somehow in a way similar to what XOR function does. After that, finding node's neighboring nodes is a trivial task.
Hope this helps. Oh by the way look to HyperDex, new searchable distributed datastore closely tied to euclidian metric, might help...