diff --git a/content/posts/birdnet_homeassistant.md b/content/posts/birdnet_homeassistant.md index e7fd833..04965ae 100644 --- a/content/posts/birdnet_homeassistant.md +++ b/content/posts/birdnet_homeassistant.md @@ -27,7 +27,9 @@ cover: hidden: true # only hide on current single page --- -_This is Part One of a Two Part Series. You can find Part Two, here._ +This is Part One of a Two Part Series. You can find Part Two, [here.]({{}}) + +**Update: 10/11/2023. A huge thanks to Mastodon User [e_mobile2014](https://mastodon.social/@e_mobil2014) who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant!** ## What you will need @@ -166,9 +168,9 @@ adding `print()` statements at various points, you'll notice that the payload is ```json { - "payload": { - "data": "data" - } + "payload": { + "data": "data" + } } ``` @@ -180,8 +182,7 @@ grab the string by their index. If you remember what [we did above]({{}} _Note: Full Transparency that I only learned about this after reading through BirdNET-Pi's code base. Full credit goes to [mcguirepr89](https://github.com/mcguirepr89). For additional reference, here is Flickr's [official page on construction photo image URLS](https://www.flickr.com/services/api/misc.urls.html)_ +{{< /box >}} With this response, we now have the variables we need to construct the URL to actually render the image. Those variables are: Farm ID, Server ID, ID and Secret. I haven't yet looked into why we need "farm" when the official documentation doesn't state @@ -255,8 +258,54 @@ from Flickr. attributes={"image": image_url}) ``` -In Part 2 of this article, we'll take a look at Home Assistant, see what these sensors look like, and create a rudimentary -dashboard. +## Importing MQTT Sensors into HomeAssistant + +Now that we have all the sensors defined and communicating via MQTT, we have one more step to import them into HomeAssistant. +[This MQTT documentation](https://www.home-assistant.io/integrations/mqtt/) by HomeAssistant is good to read about if you +need a broker setup. I will not be going over the broker in this tutorial, but may add one in the future. I tend to like the +yaml configuration for HomeAssistant, so for the sake of this guide, I'll be referencing the [manual configuration of MQTT +items and sensors](https://www.home-assistant.io/integrations/mqtt/#manual-configured-mqtt-items). + +To add the sensors from above, open up your `configuration.yaml` file in your favorite editor. You'll then want to add the +mqtt platform and domain: + +```yaml +mqtt: + - { domain }: +``` + +For the BirdNet sensors, we will be using a single domain: `sensor`. Feel free to copy and paste my config from below, but +make sure the names of each entity align with your needs, syntax, and nomenclature/system. + +**Full MQTT Sensors in Configuration.yml** + +```yaml +mqtt: + sensor: + - name: "Bird Common Name" + state_topic: "birdnet/sensors/common_name" + - name: "Bird Science Name" + state_topic: "birdnet/sensors/science_name" + - name: "Bird Time Seen" + state_topic: "birdnet/sensors/time_seen" + - name: "Bird Date Seen" + state_topic: "birdnet/sensors/date_seen" + - name: "Bird Confidence" + state_topic: "birdnet/sensors/confidence" + value_template: '{{ (value|float(0) *100) | round(1) }}' + unit_of_measurement: '%' +``` + +You might be looking at the list above and wondering where the Flickr and Wikipedia Description entities are. They were +already created by the AppDaemon script! Specifically, `self.hassapi.set_state()` function will either update the state for +an exisiting entity or, if the entity doesn't exist, it will create a new one. + +For the rest of the mqtt payloads, we need HomeAssistant to create them as they come in, which is why we add the above +code block to our HomeAssistant configuration file. To be clear, you _do not_ need to add the Wikipedia and Flickr sensors to +HA's configuration file! + +By this point, you should have successfully created 7 new sensors in HomeAssistant. In Part 2 of this article, we'll take a +look at Home Assistant, see what these sensors look like, and create a rudimentary dashboard. ## Birdnet AppDaemon Script @@ -313,3 +362,13 @@ class birdnet(adbase.ADBase): attributes={"image": image_url}) ``` + + diff --git a/public/index.html b/public/index.html index a85e7f2..4f14a9a 100644 --- a/public/index.html +++ b/public/index.html @@ -166,9 +166,10 @@ The best way to do this is by just type e from any screen in the HomeAssistant U

This is Part One of a Two Part Series. You can find Part Two, here. -What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me....

+Update: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant! +What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used....

-
September 30, 2023 · 10 min · 1953 words · Me
+
September 30, 2023 · 11 min · 2296 words · Me
diff --git a/public/posts.html b/public/posts.html index c86a05f..32c0653 100644 --- a/public/posts.html +++ b/public/posts.html @@ -140,9 +140,10 @@ The best way to do this is by just type e from any screen in the HomeAssistant U

This is Part One of a Two Part Series. You can find Part Two, here. -What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me....

+Update: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant! +What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used....

-
September 30, 2023 · 10 min · 1953 words · Me
+
September 30, 2023 · 11 min · 2296 words · Me
diff --git a/public/posts/birdnet_homeassistant.html b/public/posts/birdnet_homeassistant.html index 8d21bd6..e4164b4 100644 --- a/public/posts/birdnet_homeassistant.html +++ b/public/posts/birdnet_homeassistant.html @@ -78,8 +78,8 @@ if (!doNotTrack) { "keywords": [ "homeassistant", "python", "diy" ], - "articleBody": "This is Part One of a Two Part Series. You can find Part Two, here.\nWhat you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me. Since I’m already running an ADS-B antenna with Flight Aware, I figured this next project would deal with radio waves/transmissions. Instead, to my amazement, I discovered BirdNET-Pi!\nWhat is BirdNET-Pi? In case you didn’t click the links above, BirdNET-Pi is an app built specifically made for Rapsberry Pi devices, that builds off the BirdNET Framework. BirdNET is one of the most advanced acoustic monitoring tools available for passively monitoring bird diversity populations. Where BirdNET-Pi takes it to the next level is the ability to setup an SBC - hopefully enclosed in a waterproof space! - and monitor birds in your local environment over time.\nI think this project is beyond neat. It runs a bit slow on a Raspberry Pi 3, but overall it runs smoothly. I was even able to contribute a PR to the project in April when I noticed a bug in the platform after a hard reset of my Pi.\nBirdNET-PI Notification Setup - MQTT Once you have BirdNET-Pi up and running, you’ll need to head over to the Settings and setup the correct MQTT payloads. Here are the possible variables you can pass in an MQTT payload:\n$sciname: Scientific Name $comname: Common Name $confidence: Confidence Score $confidencepct: Confidence Score as a percentage (eg. 0.91 =\u003e 91) $listenurl: A link to the detection $date: Date $time: Time $week: Week $latitude: Latitude $longitude: Longitude $cutoff: Minimum Confidence set in “Advanced Settings” $sens: Sigmoid Sensitivity set in “Advanced Settings” $overlap: Overlap set in “Advanced Settings” $flickrimage: A preview image of the detected species from Flickr. Set your API key below. For our purposes, we will only be using $comname, $sciname, $date, $time, $week, and $confidence. However, this entire process is extremely customizable, which you’ll learn more about in the AppDaemon section. Please expand on it and include information that is pertinent to your own uses.\nHere is how I’ve setup my MQTT payload from BirdNET-Pi Settings:\nHere it is in text form:\nNotification Title: $comname, Notification Body: $sciname, $date, $time, $week, $confidence [ ] Notify each new infrequent species detection (\u003c 5 visits per week) [ ] Notify each new species first detection of the day [X] Notify each new detection [X] Send weekly report Minimum time between notifications of the same species (sec): 5 To test my MQTT notifications, I use the iOS client “MQTTool”. After signing up, head to “Subscribe” and type birdnet as the topic and then click Subscribe. If everything is setup correctly and there are birds being recorded by the BirdNET-Pi’s microphone, you should start seeing those detections in the MQTTool app. If so, fantastic news! Let’s move onto AppDaemon.\nAppDaemon Script Now that we have the Pi communicating via MQTT, it’s time to get that information into HomeAssistant. I’ve shared the full script at the bottom of this page, but let’s jump into each section. This is not a full tutorial of how to use AppDaemon, but it may help fill in any knowledge gaps with the system.\nImports First, we’re going to import time and requests. We’re going to use time as a backup to the $time component in the payload. This can be helpful to see if there delays, or if BirdNET-Pi stopped detecting. We’re then going to use requests to pull from Wikipedia’s API and grab a description for our HomeAssistant Dashboard.\nClass Definition To start any AppDaemon app, you need to include a Class that is defined in the apps.yaml file. This is also where we initialize and define the various items that will be used in the remainder of the script.\nclass birdnet(adbase.ADBase): def initialize(self): self.hassapi = self.get_plugin_api(\"HASS\") self.adapi = self.get_ad_api() self.mqttapi = self.get_plugin_api(\"MQTT\") self.birdnet_mqtt = \"birdnet\" self.mqttapi.listen_event( self.birdnet_message, \"MQTT_MESSAGE\", topic=self.birdnet_mqtt ) For this script, we need to use a lot of the AppDaemon APIs across more than just HomeAssistant, so we’re going to be using ADBase. By using that, we can initialize the various APIs, which we do in the next 3 lines. In these 3 lines we need to get access to HomeAssistant’s APIs, AppDaemon’s APIs, and MQTT APIs - the first and third items are plugins of AppDaemon, and AppDaemon is… well… AppDaemon! Here are a few reference docs:\nMQTT AppDaemon API HomeAssistant AppDaemon API AppDaemon API These will indispensable to you as you leverage AppDaemon and expand this little script.\nOnce we have access to that, we need to setup the main topic for MQTT from BirdNET-Pi and finally, what event we are listening for that will trigger the functions in the rest of the script. self.birdnet_mqtt = \"birdnet\" is the definition for the MQTT topic. Let’s breakdown the last line of the class.\nHere’s a breakdown of each of the items in that last line. You can find the official documentation here.\nself.mqttapi.listen_event - this is what we use in AppDaemon to listen for an MQTT event in order to trigger a function. self.birdnet_message - the name of the function you’d like to trigger \"MQTT_MESSAGE\" - The default event in AppDaemon’s MQTT API plugin. This is used because MQTT doesn’t keep a state in this plugin. topic=self.birdnet_mqtt - The topic that will be received to trigger the function. Defined on the previous line. In other words, what we are telling AppDaemon is the following: “When AppDaemon’s MQTT API plugin receives a message with the topic of ‘birdnet’, run the function birdnet_message.”\nbirdnet_message Function Part 1: Variables Management Now we get into our first function of the script. The first portion of this script is splitting up the payload that we defined from the BirdNET-Pi UI into individual variables that we can better manage later on. If you test this script out by adding print() statements at various points, you’ll notice that the payload is received with the following json formatting:\n{ \"payload\": { \"data\": \"data\" } } As such, we need to look inside the payload to begin grabbing the data. The pre_split variable is now just looking at the data inside the payload and the rest of the variables take all the date into the payload, split it by the comma, and then grab the string by their index. If you remember what we did above above, you’ll see that we have the various BirdNET information at each of the indexes in the AppDaemon script - 0 through 5.\nPart 2: Re-Publishing MQTT Payloads This next section is shooting all the variables we just defined back via MQTT. The reason why we do it this way is because we need HomeAssistant to grab each of these variables as individual sensors. BirdNET doesn’t give us that capability - it’s a single message with all the information in one. [Here is the documentation from AppDaemon](## BirdNET-PI Notification Setup - MQTT ) on mqtt_publish. Later on, I’ll show you how to ensure that HomeAssistant takes those topic payloads and adds them as entities in your HA setup.\nPart 3: Wikipedia Sensor The next eight lines are a fairly straightforward API call to Wikipedia. We start out by passing the science_name into the URL. The rest of the flags that we are passing into the URL comes from Wikipedia’s Docs. url = f\"https://en.wikipedia.org/w/api.php?format=json\u0026action=query\u0026prop=extracts\u0026exintro\u0026explaintext\u0026redirects=1\u0026titles={science_name}\"\nOnce that’s done we call it with response.get(url) and format it with response.json(). Wikipedia returns the json payload with the top level of query (which was our action in the url ;) ), and we’re looking for the value within that query.\nAll that’s left is to take that query value and push it to HomeAssistant! We can do that with the self.hassapi.set_state function. Within the parenthesis we define the name of the sensor (sensor.birdnet_wiki), what it’s state should be (on), and any attributes associated with the entity. Since we can’t assign a long description to the basic status of the entity, we’re adding an attribute with the key of description and the value will be the wikipedia description garnered from the API call.\nurl = f\"https://en.wikipedia.org/w/api.php?format=json\u0026action=query\u0026prop=extracts\u0026exintro\u0026explaintext\u0026redirects=1\u0026titles={science_name}\" response = requests.get(url) response = response.json() for value in response['query']['pages']: wiki_desc = response['query']['pages'][value]['extract'] self.hassapi.set_state(\"sensor.birdnet_wiki\", state='on', attributes = {\"description\": wiki_desc}) Part 4: Generate Picture for Detection (Optional) This part is optional but I noticed that BirdNET-Pi was already grabbing a Flickr Picture for it’s front end, so I took the code from the BirdNET code base and adjusted it a bit for my needs. This will work very similarly to the Wikipedia API call, the main difference here being that you need an API key for Flickr. You can find more information here.\nGiven Flickr’s fairly robust API, by passing in the detected bird’s common name, we get amazing results from the community of various pictures of the same species of bird. Ever since I’ve set this up, I’ve not seen a mislabeled picture in my dashboard!\nThe most confusion portion of this section is the image_url as you’ll notice a bunch of data[\"value\"] strings at various portions of the URL. The short answer to this is in the previous line with the data variable. A successful query has Flickr returning a large payload of information. We’re specifically using this Flickr API endpoint. While you can pass a lot of variables for your needs, if you scroll down, you can see that the example response contains multiple photos in a single response. We’re passing per_page=5 to limit some of those response items. Left out of that response, though, is a one-stop-shop for a URL to that photo. Thankfully, Flickr can help us put together a URL from the data in the response.\nNote: Full Transparency that I only learned about this after reading through BirdNET-Pi’s code base. Full credit goes to mcguirepr89. For additional reference, here is Flickr’s official page on construction photo image URLS\nWith this response, we now have the variables we need to construct the URL to actually render the image. Those variables are: Farm ID, Server ID, ID and Secret. I haven’t yet looked into why we need “farm” when the official documentation doesn’t state anything about it.\nAlmost there! We now do the same as we did with the Wikipedia API response. We create a sensor in HomeAssistant! We’re calling this sensor sensor.birdpic, ensuring the state=on, and giving it the attributes of the image_url as garnered from Flickr.\nheaders = {'User-Agent': 'Python_Flickr/1.0'} flickr_api = \"enter_your_api_key\" flickr_url = f\"https://www.flickr.com/services/rest/?method=flickr.photos.search\u0026api_key={flickr_api}\u0026text={common_name} bird\u0026sort=relevance\u0026per_page=5\u0026media=photos\u0026format=json\u0026nojsoncallback=1\" flickr_resp = requests.get(url=flickr_url, headers=headers) data = flickr_resp.json()[\"photos\"][\"photo\"][0] image_url = 'https://farm'+str(data[\"farm\"])+'.static.flickr.com/'+str(data[\"server\"])+'/'+str(data[\"id\"])+'_'+str(data[\"secret\"])+'_n.jpg' self.hassapi.set_state(\"sensor.birdpic\", state='on', attributes={\"image\": image_url}) In Part 2 of this article, we’ll take a look at Home Assistant, see what these sensors look like, and create a rudimentary dashboard.\nBirdnet AppDaemon Script import time import requests class birdnet(adbase.ADBase): def initialize(self): self.hassapi = self.get_plugin_api(\"HASS\") self.adapi = self.get_ad_api() self.mqttapi = self.get_plugin_api(\"MQTT\") self.birdnet_mqtt = \"birdnet\" self.mqttapi.listen_event( self.birdnet_message, \"MQTT_MESSAGE\", topic=self.birdnet_mqtt ) def birdnet_message(self, event_name, data, kwargs): pre_split = data[\"payload\"] common_name = pre_split.split(',')[0].strip() science_name = pre_split.split(',')[1].strip() date_seen = pre_split.split(',')[2].strip() time_seen = pre_split.split(',')[3].strip() week_seen = pre_split.split(',')[4].strip() confidence = pre_split.split(',')[5].strip() # print(f\"A {common_name} was seen on {date_seen} at {time_seen}. Confidence is {confidence}.\") self.mqttapi.mqtt_publish(\"birdnet/sensors/common_name\", common_name) self.mqttapi.mqtt_publish(\"birdnet/sensors/science_name\", science_name) self.mqttapi.mqtt_publish(\"birdnet/sensors/time_seen\", time_seen) self.mqttapi.mqtt_publish(\"birdnet/sensors/date_seen\", date_seen) self.mqttapi.mqtt_publish(\"birdnet/sensors/confidence\", confidence) url = f\"https://en.wikipedia.org/w/api.php?format=json\u0026action=query\u0026prop=extracts\u0026exintro\u0026explaintext\u0026redirects=1\u0026titles={science_name}\" response = requests.get(url) response = response.json() for value in response['query']['pages']: wiki_desc = response['query']['pages'][value]['extract'] self.hassapi.set_state(\"sensor.birdnet_wiki\", state='on', attributes = {\"description\": wiki_desc}) headers = {'User-Agent': 'Python_Flickr/1.0'} flickr_api = \"enter_your_api_key\" flickr_url = f\"https://www.flickr.com/services/rest/?method=flickr.photos.search\u0026api_key={flickr_api}\u0026text={common_name} bird\u0026sort=relevance\u0026per_page=5\u0026media=photos\u0026format=json\u0026nojsoncallback=1\" flickr_resp = requests.get(url=flickr_url, headers=headers) data = flickr_resp.json()[\"photos\"][\"photo\"][0] image_url = 'https://farm'+str(data[\"farm\"])+'.static.flickr.com/'+str(data[\"server\"])+'/'+str(data[\"id\"])+'_'+str(data[\"secret\"])+'_n.jpg' self.hassapi.set_state(\"sensor.birdpic\", state='on', attributes={\"image\": image_url}) ", - "wordCount" : "1953", + "articleBody": "This is Part One of a Two Part Series. You can find Part Two, here.\nUpdate: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant!\nWhat you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me. Since I’m already running an ADS-B antenna with Flight Aware, I figured this next project would deal with radio waves/transmissions. Instead, to my amazement, I discovered BirdNET-Pi!\nWhat is BirdNET-Pi? In case you didn’t click the links above, BirdNET-Pi is an app built specifically made for Rapsberry Pi devices, that builds off the BirdNET Framework. BirdNET is one of the most advanced acoustic monitoring tools available for passively monitoring bird diversity populations. Where BirdNET-Pi takes it to the next level is the ability to setup an SBC - hopefully enclosed in a waterproof space! - and monitor birds in your local environment over time.\nI think this project is beyond neat. It runs a bit slow on a Raspberry Pi 3, but overall it runs smoothly. I was even able to contribute a PR to the project in April when I noticed a bug in the platform after a hard reset of my Pi.\nBirdNET-PI Notification Setup - MQTT Once you have BirdNET-Pi up and running, you’ll need to head over to the Settings and setup the correct MQTT payloads. Here are the possible variables you can pass in an MQTT payload:\n$sciname: Scientific Name $comname: Common Name $confidence: Confidence Score $confidencepct: Confidence Score as a percentage (eg. 0.91 =\u003e 91) $listenurl: A link to the detection $date: Date $time: Time $week: Week $latitude: Latitude $longitude: Longitude $cutoff: Minimum Confidence set in “Advanced Settings” $sens: Sigmoid Sensitivity set in “Advanced Settings” $overlap: Overlap set in “Advanced Settings” $flickrimage: A preview image of the detected species from Flickr. Set your API key below. For our purposes, we will only be using $comname, $sciname, $date, $time, $week, and $confidence. However, this entire process is extremely customizable, which you’ll learn more about in the AppDaemon section. Please expand on it and include information that is pertinent to your own uses.\nHere is how I’ve setup my MQTT payload from BirdNET-Pi Settings:\nHere it is in text form:\nNotification Title: $comname, Notification Body: $sciname, $date, $time, $week, $confidence [ ] Notify each new infrequent species detection (\u003c 5 visits per week) [ ] Notify each new species first detection of the day [X] Notify each new detection [X] Send weekly report Minimum time between notifications of the same species (sec): 5 To test my MQTT notifications, I use the iOS client “MQTTool”. After signing up, head to “Subscribe” and type birdnet as the topic and then click Subscribe. If everything is setup correctly and there are birds being recorded by the BirdNET-Pi’s microphone, you should start seeing those detections in the MQTTool app. If so, fantastic news! Let’s move onto AppDaemon.\nAppDaemon Script Now that we have the Pi communicating via MQTT, it’s time to get that information into HomeAssistant. I’ve shared the full script at the bottom of this page, but let’s jump into each section. This is not a full tutorial of how to use AppDaemon, but it may help fill in any knowledge gaps with the system.\nImports First, we’re going to import time and requests. We’re going to use time as a backup to the $time component in the payload. This can be helpful to see if there delays, or if BirdNET-Pi stopped detecting. We’re then going to use requests to pull from Wikipedia’s API and grab a description for our HomeAssistant Dashboard.\nClass Definition To start any AppDaemon app, you need to include a Class that is defined in the apps.yaml file. This is also where we initialize and define the various items that will be used in the remainder of the script.\nclass birdnet(adbase.ADBase): def initialize(self): self.hassapi = self.get_plugin_api(\"HASS\") self.adapi = self.get_ad_api() self.mqttapi = self.get_plugin_api(\"MQTT\") self.birdnet_mqtt = \"birdnet\" self.mqttapi.listen_event( self.birdnet_message, \"MQTT_MESSAGE\", topic=self.birdnet_mqtt ) For this script, we need to use a lot of the AppDaemon APIs across more than just HomeAssistant, so we’re going to be using ADBase. By using that, we can initialize the various APIs, which we do in the next 3 lines. In these 3 lines we need to get access to HomeAssistant’s APIs, AppDaemon’s APIs, and MQTT APIs - the first and third items are plugins of AppDaemon, and AppDaemon is… well… AppDaemon! Here are a few reference docs:\nMQTT AppDaemon API HomeAssistant AppDaemon API AppDaemon API These will indispensable to you as you leverage AppDaemon and expand this little script.\nOnce we have access to that, we need to setup the main topic for MQTT from BirdNET-Pi and finally, what event we are listening for that will trigger the functions in the rest of the script. self.birdnet_mqtt = \"birdnet\" is the definition for the MQTT topic. Let’s breakdown the last line of the class.\nHere’s a breakdown of each of the items in that last line. You can find the official documentation here.\nself.mqttapi.listen_event - this is what we use in AppDaemon to listen for an MQTT event in order to trigger a function. self.birdnet_message - the name of the function you’d like to trigger \"MQTT_MESSAGE\" - The default event in AppDaemon’s MQTT API plugin. This is used because MQTT doesn’t keep a state in this plugin. topic=self.birdnet_mqtt - The topic that will be received to trigger the function. Defined on the previous line. In other words, what we are telling AppDaemon is the following: “When AppDaemon’s MQTT API plugin receives a message with the topic of ‘birdnet’, run the function birdnet_message.”\nbirdnet_message Function Part 1: Variables Management Now we get into our first function of the script. The first portion of this script is splitting up the payload that we defined from the BirdNET-Pi UI into individual variables that we can better manage later on. If you test this script out by adding print() statements at various points, you’ll notice that the payload is received with the following json formatting:\n{ \"payload\": { \"data\": \"data\" } } As such, we need to look inside the payload to begin grabbing the data. The pre_split variable is now just looking at the data inside the payload and the rest of the variables take all the date into the payload, split it by the comma, and then grab the string by their index. If you remember what we did above above, you’ll see that we have the various BirdNET information at each of the indexes in the AppDaemon script - 0 through 5.\nPart 2: Re-Publishing MQTT Payloads This next section is shooting all the variables we just defined back via MQTT. The reason why we do it this way is because we need HomeAssistant to grab each of these variables as individual sensors. BirdNET doesn’t give us that capability - it’s a single message with all the information in one. Here is the documentation from AppDaemon on mqtt_publish. Later on, I’ll show you how to ensure that HomeAssistant takes those topic payloads and adds them as entities in your HA setup.\nPart 3: Wikipedia Sensor The next eight lines are a fairly straightforward API call to Wikipedia. We start out by passing the science_name into the URL. The rest of the flags that we are passing into the URL comes from Wikipedia’s Docs. url = f\"https://en.wikipedia.org/w/api.php?format=json\u0026action=query\u0026prop=extracts\u0026exintro\u0026explaintext\u0026redirects=1\u0026titles={science_name}\"\nOnce that’s done we call it with response.get(url) and format it with response.json(). Wikipedia returns the json payload with the top level of query (which was our action in the url ;) ), and we’re looking for the value within that query.\nAll that’s left is to take that query value and push it to HomeAssistant! We can do that with the self.hassapi.set_state function. Within the parenthesis we define the name of the sensor (sensor.birdnet_wiki), what it’s state should be (on), and any attributes associated with the entity. Since we can’t assign a long description to the basic status of the entity, we’re adding an attribute with the key of description and the value will be the wikipedia description garnered from the API call.\nurl = f\"https://en.wikipedia.org/w/api.php?format=json\u0026action=query\u0026prop=extracts\u0026exintro\u0026explaintext\u0026redirects=1\u0026titles={science_name}\" response = requests.get(url) response = response.json() for value in response['query']['pages']: wiki_desc = response['query']['pages'][value]['extract'] self.hassapi.set_state(\"sensor.birdnet_wiki\", state='on', attributes = {\"description\": wiki_desc}) Part 4: Generate Picture for Detection (Optional) This part is optional but I noticed that BirdNET-Pi was already grabbing a Flickr Picture for it’s front end, so I took the code from the BirdNET code base and adjusted it a bit for my needs. This will work very similarly to the Wikipedia API call, the main difference here being that you need an API key for Flickr. You can find more information here.\nGiven Flickr’s fairly robust API, by passing in the detected bird’s common name, we get amazing results from the community of various pictures of the same species of bird. Ever since I’ve set this up, I’ve not seen a mislabeled picture in my dashboard!\nThe most confusion portion of this section is the image_url as you’ll notice a bunch of data[\"value\"] strings at various portions of the URL. The short answer to this is in the previous line with the data variable. A successful query has Flickr returning a large payload of information. We’re specifically using this Flickr API endpoint. While you can pass a lot of variables for your needs, if you scroll down, you can see that the example response contains multiple photos in a single response. We’re passing per_page=5 to limit some of those response items. Left out of that response, though, is a one-stop-shop for a URL to that photo. Thankfully, Flickr can help us put together a URL from the data in the response.\nNote: Full Transparency that I only learned about this after reading through BirdNET-Pi’s code base. Full credit goes to mcguirepr89. For additional reference, here is Flickr’s official page on construction photo image URLS\nWith this response, we now have the variables we need to construct the URL to actually render the image. Those variables are: Farm ID, Server ID, ID and Secret. I haven’t yet looked into why we need “farm” when the official documentation doesn’t state anything about it.\nAlmost there! We now do the same as we did with the Wikipedia API response. We create a sensor in HomeAssistant! We’re calling this sensor sensor.birdpic, ensuring the state=on, and giving it the attributes of the image_url as garnered from Flickr.\nheaders = {'User-Agent': 'Python_Flickr/1.0'} flickr_api = \"enter_your_api_key\" flickr_url = f\"https://www.flickr.com/services/rest/?method=flickr.photos.search\u0026api_key={flickr_api}\u0026text={common_name} bird\u0026sort=relevance\u0026per_page=5\u0026media=photos\u0026format=json\u0026nojsoncallback=1\" flickr_resp = requests.get(url=flickr_url, headers=headers) data = flickr_resp.json()[\"photos\"][\"photo\"][0] image_url = 'https://farm'+str(data[\"farm\"])+'.static.flickr.com/'+str(data[\"server\"])+'/'+str(data[\"id\"])+'_'+str(data[\"secret\"])+'_n.jpg' self.hassapi.set_state(\"sensor.birdpic\", state='on', attributes={\"image\": image_url}) Importing MQTT Sensors into HomeAssistant Now that we have all the sensors defined and communicating via MQTT, we have one more step to import them into HomeAssistant. This MQTT documentation by HomeAssistant is good to read about if you need a broker setup. I will not be going over the broker in this tutorial, but may add one in the future. I tend to like the yaml configuration for HomeAssistant, so for the sake of this guide, I’ll be referencing the manual configuration of MQTT items and sensors.\nTo add the sensors from above, open up your configuration.yaml file in your favorite editor. You’ll then want to add the mqtt platform and domain:\nmqtt: - { domain }: For the BirdNet sensors, we will be using a single domain: sensor. Feel free to copy and paste my config from below, but make sure the names of each entity align with your needs, syntax, and nomenclature/system.\nFull MQTT Sensors in Configuration.yml\nmqtt: sensor: - name: \"Bird Common Name\" state_topic: \"birdnet/sensors/common_name\" - name: \"Bird Science Name\" state_topic: \"birdnet/sensors/science_name\" - name: \"Bird Time Seen\" state_topic: \"birdnet/sensors/time_seen\" - name: \"Bird Date Seen\" state_topic: \"birdnet/sensors/date_seen\" - name: \"Bird Confidence\" state_topic: \"birdnet/sensors/confidence\" value_template: '{{ (value|float(0) *100) | round(1) }}' unit_of_measurement: '%' You might be looking at the list above and wondering where the Flickr and Wikipedia Description entities are. They were already created by the AppDaemon script! Specifically, self.hassapi.set_state() function will either update the state for an exisiting entity or, if the entity doesn’t exist, it will create a new one.\nFor the rest of the mqtt payloads, we need HomeAssistant to create them as they come in, which is why we add the above code block to our HomeAssistant configuration file. To be clear, you do not need to add the Wikipedia and Flickr sensors to HA’s configuration file!\nBy this point, you should have successfully created 7 new sensors in HomeAssistant. In Part 2 of this article, we’ll take a look at Home Assistant, see what these sensors look like, and create a rudimentary dashboard.\nBirdnet AppDaemon Script import time import requests class birdnet(adbase.ADBase): def initialize(self): self.hassapi = self.get_plugin_api(\"HASS\") self.adapi = self.get_ad_api() self.mqttapi = self.get_plugin_api(\"MQTT\") self.birdnet_mqtt = \"birdnet\" self.mqttapi.listen_event( self.birdnet_message, \"MQTT_MESSAGE\", topic=self.birdnet_mqtt ) def birdnet_message(self, event_name, data, kwargs): pre_split = data[\"payload\"] common_name = pre_split.split(',')[0].strip() science_name = pre_split.split(',')[1].strip() date_seen = pre_split.split(',')[2].strip() time_seen = pre_split.split(',')[3].strip() week_seen = pre_split.split(',')[4].strip() confidence = pre_split.split(',')[5].strip() # print(f\"A {common_name} was seen on {date_seen} at {time_seen}. Confidence is {confidence}.\") self.mqttapi.mqtt_publish(\"birdnet/sensors/common_name\", common_name) self.mqttapi.mqtt_publish(\"birdnet/sensors/science_name\", science_name) self.mqttapi.mqtt_publish(\"birdnet/sensors/time_seen\", time_seen) self.mqttapi.mqtt_publish(\"birdnet/sensors/date_seen\", date_seen) self.mqttapi.mqtt_publish(\"birdnet/sensors/confidence\", confidence) url = f\"https://en.wikipedia.org/w/api.php?format=json\u0026action=query\u0026prop=extracts\u0026exintro\u0026explaintext\u0026redirects=1\u0026titles={science_name}\" response = requests.get(url) response = response.json() for value in response['query']['pages']: wiki_desc = response['query']['pages'][value]['extract'] self.hassapi.set_state(\"sensor.birdnet_wiki\", state='on', attributes = {\"description\": wiki_desc}) headers = {'User-Agent': 'Python_Flickr/1.0'} flickr_api = \"enter_your_api_key\" flickr_url = f\"https://www.flickr.com/services/rest/?method=flickr.photos.search\u0026api_key={flickr_api}\u0026text={common_name} bird\u0026sort=relevance\u0026per_page=5\u0026media=photos\u0026format=json\u0026nojsoncallback=1\" flickr_resp = requests.get(url=flickr_url, headers=headers) data = flickr_resp.json()[\"photos\"][\"photo\"][0] image_url = 'https://farm'+str(data[\"farm\"])+'.static.flickr.com/'+str(data[\"server\"])+'/'+str(data[\"id\"])+'_'+str(data[\"secret\"])+'_n.jpg' self.hassapi.set_state(\"sensor.birdpic\", state='on', attributes={\"image\": image_url}) ", + "wordCount" : "2296", "inLanguage": "en", "image":"/birdnet-homeassistant.png","datePublished": "2023-09-30T11:21:55-04:00", "dateModified": "2023-09-30T11:21:55-04:00", @@ -158,7 +158,7 @@ if (!doNotTrack) {
Learn how to take BirdNET-Pi Detections to create and display entities in HomeAssistant.
-
September 30, 2023 · 10 min · 1953 words · Me +
September 30, 2023 · 11 min · 2296 words · Me
@@ -180,6 +180,7 @@ if (!doNotTrack) {
  • birdnet_message Function
    • +
  • Importing MQTT Sensors into HomeAssistant
  • Birdnet AppDaemon Script
    • @@ -187,7 +188,8 @@ if (!doNotTrack) {
    -

    This is Part One of a Two Part Series. You can find Part Two, here.

    +

    This is Part One of a Two Part Series. You can find Part Two, here.

    +

    Update: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant!

    What you will need

    • BirdNET-Pi
      • @@ -296,9 +298,9 @@ topic of ‘birdnet’, run the function birdnet_message.&r defined from the BirdNET-Pi UI into individual variables that we can better manage later on. If you test this script out by adding print() statements at various points, you’ll notice that the payload is received with the following json formatting:

      {
-	"payload": {
-		"data": "data"
-	}
+ "payload": {
+  "data": "data"
+ }
 }

      As such, we need to look inside the payload to begin grabbing the data. The pre_split variable is now just looking at the data inside the payload and the rest of the variables take all the date into the payload, split it by the comma, and then @@ -306,8 +308,7 @@ grab the string by their index. If you remember what Part 2: Re-Publishing MQTT Payloads

      This next section is shooting all the variables we just defined back via MQTT. The reason why we do it this way is because we need HomeAssistant to grab each of these variables as individual sensors. BirdNET doesn’t give us that capability - it’s a -single message with all the information in one. [Here is the documentation from AppDaemon](## BirdNET-PI Notification Setup - MQTT -) on mqtt_publish. Later on, I’ll show you how to ensure that HomeAssistant takes those topic payloads and adds them as +single message with all the information in one. Here is the documentation from AppDaemon on mqtt_publish. Later on, I’ll show you how to ensure that HomeAssistant takes those topic payloads and adds them as entities in your HA setup.

      Part 3: Wikipedia Sensor

      The next eight lines are a fairly straightforward API call to Wikipedia. We start @@ -343,9 +344,111 @@ Flickr API endpoint. While you can pass a lot of variables for your needs, if yo response contains multiple photos in a single response. We’re passing per_page=5 to limit some of those response items. Left out of that response, though, is a one-stop-shop for a URL to that photo. Thankfully, Flickr can help us put together a URL from the data in the response.

      -

      Note: Full Transparency that I only learned about this after reading through BirdNET-Pi’s code base. Full credit goes to + + + + + + + + + + + + + + + + + + +

      + + + +

      Note: Full Transparency that I only learned about this after reading through BirdNET-Pi’s code base. Full credit goes to mcguirepr89. For additional reference, here is Flickr’s official page on construction photo image URLS

      +
      +

      With this response, we now have the variables we need to construct the URL to actually render the image. Those variables are: Farm ID, Server ID, ID and Secret. I haven’t yet looked into why we need “farm” when the official documentation doesn’t state anything about it.

      @@ -362,8 +465,41 @@ from Flickr.

      self.hassapi.set_state("sensor.birdpic", state='on', attributes={"image": image_url}) -

    In Part 2 of this article, we’ll take a look at Home Assistant, see what these sensors look like, and create a rudimentary -dashboard.

    +

    Importing MQTT Sensors into HomeAssistant

    +

    Now that we have all the sensors defined and communicating via MQTT, we have one more step to import them into HomeAssistant. +This MQTT documentation by HomeAssistant is good to read about if you +need a broker setup. I will not be going over the broker in this tutorial, but may add one in the future. I tend to like the +yaml configuration for HomeAssistant, so for the sake of this guide, I’ll be referencing the manual configuration of MQTT +items and sensors.

    +

    To add the sensors from above, open up your configuration.yaml file in your favorite editor. You’ll then want to add the +mqtt platform and domain:

    +
    mqtt:
+  - { domain }:
+

    For the BirdNet sensors, we will be using a single domain: sensor. Feel free to copy and paste my config from below, but +make sure the names of each entity align with your needs, syntax, and nomenclature/system.

    +

    Full MQTT Sensors in Configuration.yml

    +
    mqtt:
+  sensor:
+    - name: "Bird Common Name"
+      state_topic: "birdnet/sensors/common_name"
+    - name: "Bird Science Name"
+      state_topic: "birdnet/sensors/science_name"
+    - name: "Bird Time Seen"
+      state_topic: "birdnet/sensors/time_seen"
+    - name: "Bird Date Seen"
+      state_topic: "birdnet/sensors/date_seen"
+    - name: "Bird Confidence"
+      state_topic: "birdnet/sensors/confidence"
+      value_template: '{{ (value|float(0) *100) | round(1) }}'
+      unit_of_measurement: '%'
+

    You might be looking at the list above and wondering where the Flickr and Wikipedia Description entities are. They were +already created by the AppDaemon script! Specifically, self.hassapi.set_state() function will either update the state for +an exisiting entity or, if the entity doesn’t exist, it will create a new one.

    +

    For the rest of the mqtt payloads, we need HomeAssistant to create them as they come in, which is why we add the above +code block to our HomeAssistant configuration file. To be clear, you do not need to add the Wikipedia and Flickr sensors to +HA’s configuration file!

    +

    By this point, you should have successfully created 7 new sensors in HomeAssistant. In Part 2 of this article, we’ll take a +look at Home Assistant, see what these sensors look like, and create a rudimentary dashboard.

    Birdnet AppDaemon Script

    import time
 import requests
@@ -415,7 +551,16 @@ dashboard.
    
     
         self.hassapi.set_state("sensor.birdpic", state='on',
                                attributes={"image": image_url})
-
    +
    + diff --git a/public/tags/diy.html b/public/tags/diy.html index 530c8ba..8e8afce 100644 --- a/public/tags/diy.html +++ b/public/tags/diy.html @@ -125,9 +125,10 @@ The best way to do this is by just type e from any screen in the HomeAssistant U

    This is Part One of a Two Part Series. You can find Part Two, here. -What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me....

    +Update: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant! +What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used....

    -
    September 30, 2023 · 10 min · 1953 words · Me
    +
    September 30, 2023 · 11 min · 2296 words · Me
    diff --git a/public/tags/homeassistant.html b/public/tags/homeassistant.html index fbaba67..5561b0c 100644 --- a/public/tags/homeassistant.html +++ b/public/tags/homeassistant.html @@ -125,9 +125,10 @@ The best way to do this is by just type e from any screen in the HomeAssistant U

    This is Part One of a Two Part Series. You can find Part Two, here. -What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me....

    +Update: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant! +What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used....

    -
    September 30, 2023 · 10 min · 1953 words · Me
    +
    September 30, 2023 · 11 min · 2296 words · Me
    diff --git a/public/tags/python.html b/public/tags/python.html index 473d293..0a84a4e 100644 --- a/public/tags/python.html +++ b/public/tags/python.html @@ -110,9 +110,10 @@ if (!doNotTrack) {

    This is Part One of a Two Part Series. You can find Part Two, here. -What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used. I’m a big fan of any sort of passive intake of information and had been looking around for various citizen science-style projects that can capture information from the world around me....

    +Update: 10/11/2023. A huge thanks to Mastodon User e_mobile2014 who found a broken link in this guide and pointed out that I never explained how to get the mqtt sensors into HomeAssistant! +What you will need BirdNET-Pi HomeAssistant AppDaemon MQTT Broker (I use Mosquitto) Background In early 2023, at the height of the Raspberry Pi shortage I felt like a king with an extra Rpi laying around, not being used....

    -
    September 30, 2023 · 10 min · 1953 words · Me
    +
    September 30, 2023 · 11 min · 2296 words · Me