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":[[]]}]
Related
If I send a gauge to Prometheus then the payload has a timestamp and a value like:
metric_name {label="value"} 2.0 16239938546837
If I query it on Prometheus I can see a continous line. Without sending a payload for the same metric the line stops. Sending the same metric after some minutes I get another continous line, but it is not connected with the old line.
Is this fixed in Prometheus how long a timeseries last without getting an update?
I think the first answer by Marc is in a different context.
Any timeseries in prometheus goes stale in 5m by default if the collection stops - https://www.robustperception.io/staleness-and-promql. In other words, the line stops on graph (or grafana).
So if you resume the metrics collection again within 5 minutes, then it will connect the line by default. But if there is no collection for more than 5 minutes then it will show a disconnect on the graph. You can tweak that on Grafana to ignore drops but that not ideal in some cases as you do want to see when the collection stopped instead of giving the false impression that there was continuous collection. Alternatively, you can avoid the disconnect using some functions like avg_over_time(metric_name[10m]) as needed.
There is two questions here :
1. How long does prometheus keeps the data ?
This depends on the configuration you have for your storage. By default, on local storage, prometheus have a retention of 15days. You can find out more in the documentation. You can also change this value with this option : --storage.tsdb.retention.time
2. When will I have a "hole" in my graph ?
The line you see on a graph is made by joining each point from each scrape. Those scrape are done regularly based on the scrape_interval value you have in your scrape_config. So basically, if you have no data during one scrape, then you'll have a hole.
So there is no definitive answer, this depends essentially on your scrape_interval.
Note that if you're using a function that evaluate metrics for a certain amount of time, then missing one scrape will not alter your graph. For example, using a rate[5m] will not alter your graph if you scrape every 1m (as you'll have 4 other samples to do the rate).
I have the current use case:
We have a system that computes different response time metrics for messages that we want to insert in InfluxDB. This system writes JSON entries to a file.
We use telegraf with JSON plugin to extract the fields we want and insert into InfluxDB.
So far so good.
But we have an issue with 1 particular information.
The system will emit messages where mId is the Unique identifier, in the below examples we have 2 uuidXXXX and uuidYYYY:
{“meta1”:“value”, “mId”:“uuidXXXX”, “resTime1”:1232332233, “timeWeEnterBus”:startTimestamp}
{“meta1”:“value2”, “mId”:“uuidYYYY”, “resTime1”:1232331111, “timeWeEnterBus”:startTimestamp}
{“meta1”:“value”, “mId”:“uuidXXXX”, “resTime1”:1232332233, “timeWeExitBus”:endTimestamp}
{“meta1”:“value2”, “mId”:“uuidYYYY”, “resTime1”:1232331111, “timeWeEnterBus”:startTimestamp}
And what we want here is to graph the timeInBus which is equal to “timeWeExitBus-timeWeEnterBus” for each unique mId.
So my questions are:
IMU, uuid would be a field not a tag as it is unlimited, same for timeWeExitBus and timeWeEnterBus which would be numeric fields since we want to use functions on them. And timeInBus would be the measurement. Am I right ?
Is this use case a good one for Influx / Telegraf or are we misusing it for this ? IMU, it doesn’t look like a good use case to try to compute this on telegraf side, but I don’t see how to do it in InfluxDB, I initially thought ELAPSED function could help but I end up thinking it doesn’t work here
If it’s a good use case, could you point me to documentation helping implementing this ?
I can subscribe to the acceleration or angular velocity values with the movesense mobile libraries, but is there a way to change the sampling rate of the sensor?
The new movesense-device-lib (released today) has the new sensor API's that make it possible. The API's provide convenient and generic way to access all the "fast" sensors: Accelerometer, Gyroscope and Magnetic field. The paths have also been changed to make them less verbose (saves flash memory).
Here's a small intro on how the new API's work:
For each sensor there is a resource under root /Meas. /Meas/Acc, /Meas/Gyro and /Meas/Magn and they all work the same way.
Under the sensors root there is an Info resource that returns available sample rates as well as ranges. This is the result from GET'ing the /Meas/Acc/Info:
{
"SampleRates" : [13,26,52,104,208],
"Ranges" : [2,4,8,16]
}
Also under the sensors root there is a Config resource when one can GET & PUT the sensors global settings. At the moment the only setting in Accelerometer is GRange.
The data can be only SUBSCRIBED (no more GET in API), and the sample rate wanted is set as URL parameter: /Meas/Acc/{SampleRate} where the {SampleRate} is one of the values from the Info resource.
The sbuscribed data is returned in the object of the form: {timestamp, array of FloatVector3D's}. Different sample rates can return different number of measurements per notification in the array.
Word of caution: We have tested the accelerometer upto 208 Hz (as of today) so even if the API advertises higher rates, we have not yet tested how far we can push the sensor in practice.
Full Disclosure: I work for Movesense team
I'm trying to use butterworth filter. The input data comes from an "index array" module (the data is acquired through DAQ and I want to process the voltage signal which is in an array of waveforms). when I use this filter in a case structure, it doesn't work. yet, when I use the filters in the "waveform conditioning" section, there is no problem. what exactly is the difference between these two types of filters?
a little add on to my problem: the second picture is from when i tried to reassemble the initial combination, and the error happened
You are comparing offline filtering to online filtering.
In LabVIEW, the PtbyPt-VIs are intended to be used in an online setting, that is - iteratively.
For each new sample that is obtained, it would be input directly into the VI. The VI stores the states of the previous iterations to perform the filtering.
The "normal" filter VIs are intended for offline analysis and expects an array containing the full data of the signal.
The following whitepaper explains Point-by-Point-VIs. Note that this paper is quite old, so it should explain the concepts - but might be otherwise outdated.
http://www.ni.com/pdf/manuals/370152b.pdf
If VoltageBuf is an array of consecutive values of the same signal (the one that you want to filter) you only need to connect VoltageBuf directly to the filter.
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...