87 lines
3.2 KiB
TOML
87 lines
3.2 KiB
TOML
# Default settings file.
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#
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# DO NOT EDIT THIS FILE. Instead edit ../settings.toml (or create it if it doesn't exist yet).
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program_name = "LoRaWAN Signal Mapper"
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version = "v0.1"
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description = "assists in mapping LoRaWAN signal coverage"
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[database]
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### Database settings ###
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# The path to the sqlite database file. If it doesn't exist it will be created.
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filename = "lorawan.sqlite"
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# The options to pass to better-sqlite3. You probably don't need to change this.
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[database.options]
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[ttn]
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### The Things Network settings ###
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# The host to connect to via MQTT.
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# See https://www.thethingsnetwork.org/docs/applications/mqtt/api.html
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# and also "Application Overview -> Handler"
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host = "eu.thethings.network"
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# The port number to connect on.
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# The Things Network uses 1883 for plain-text, and 8883 for TLS.
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port = 8883
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# Whether to use TLS or not.
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tls = true
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# The id of The Things Network application to connect with.
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# Basically your application's name. Get this from the things network
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# console - e.g. "lorawan-signal-mapping".
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app_id = "CHANGE_THIS"
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# The access key to connect to The Things Network with.
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# Get this from the TTN console too. Click on your application, scroll to the
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# "access keys" section at the bottom of the page, and copy the value you see
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# there.
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access_key = "CHANGE_THIS"
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# The additional encryption key, in hex, generated when setting up the IoT device.
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# This is used as an exrtra layer of encryption to ensure that The Things Network does not have access to the decrypted data.
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encryption_key = "CHANGE_THIS"
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# A list of devices to monitor.
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# If a device isn't specified here, then we won't hear messages from it.
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# FUTURE: Automatically fetch a list of devices from the TTN API
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devices = [
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"CHANGE_THIS"
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]
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[ai]
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# Settings relating to the training of the AI. Note that a number of these settings can also be specified by environment variables, to aid with fiddling with the parameters to find the right settings.
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# Min / max dataset values when training the AI, since neural networks only take values between 0 and 1.
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# Note that changing these means that you've got to retrain the AIs all over again!
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rssi_min = -150
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rssi_max = 0
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# Data is streamed from the SQLite databse. The batch size specifies how many
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# rows to gather for training at once.
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# Note that the entire available dataset will eventually end up being used -
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# this setting just controls how much of ti is in memory at once.
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batch_size = 32
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# The number of epochs to train for.
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epochs = 5
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# The percentage, between 0 and 1, of data that should be set aside for validation.
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validation_split = 0.1
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# The directory to output trained AIs to, relative to the repository root.
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output_directory = "app/ais/"
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[logging]
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# The format the date displayed when logging things should take.
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# Allowed values: relative (e.g like when a Linux machine boots), absolute (e.g. like Nginx server logs), none (omits it entirely))
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date_display_mode = "relative"
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# Whether we should be verbose and log a bunch of stuff to the console.
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# Disabled by default, but useful for debugging.
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verbose = false
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# Whether we should output ANSI escape sequences to colourise the output or not.
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# Defaults to true, but you should turn it off if you're using syslog.
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colour = true
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