Middle-age Mutable Ninja Tuples is integrating with all the things!

The backend for the end-user mobile app (.NET MAUI) is integrating with Dynamics 365 via MS Dynamics Web API, to create SOS alerts and get status updates.

The backend for the Turtle back-office (Blazor web app) is communicating with Azure via MS Graph API to programatically create Azure AD users.

Both backends are retrieving access tokens for MS APIs using MS OAuth API.

The Turtle code-base (GitHub) is configured to automatically post events to Discord, such as commits and releases.

Test – data

We needed testdata to develop the functions, so we made a simple ADF pipeline that inserts “actions” every x sec (if we want to).. We also need a lot of data, since we are planning to run reports and AI, with this test-data function we can start develop.

The ADF-pipeline takes a few params so we can controll how many runs we get.

Source data:

  • SQL server
    • Table with first Names
    • Table with last names
    • Table with IncidentTypes
    • View generating random:
      • name: mixing firstname and lastname
      • incident types (as we make more incident types)
      • longitude: Random – 59.9000 – 59.9999
      • latitude: Random – 10.1000 – 10.9999

Assaults

Planned Work

TBC

Completed Work

TBC

Rules

For å ha bedre kontroll på system, uten å måtte manuelt overvåke hele døgnet, har vi implementert “Rules” i IoT Central.

Hvis temperature går under 18 grader blir en alerm aktivert, hvor det sendes ut mail relevante personer med informasjon om hva som har skjedd.

Hvis Rotation/Y overstiger 0.1 betyr det at telefon (eller skildpadden i tenkt tilfelle) er snudd opp ned. Da sendes det ut en alarm beskjed om at gitt telefon er snudd på hode.

Bildet under viser hvordan en mail ser ut når en skildpadde er snudd på opp ned.

Claimed Badge:

Flowbombing Dataverse

Bombshells elsker Dataverse og går mann av huse for å bygge opp kraftfulle datakilder som de kan bruke til å trene opp varslingssytemet sitt. Derfor bruker de Power Automate Flow for å populere dataverse med sensordata.

Ved å kalle en PAF som et restkall bruker vi Dataverse-connectoren til å legge til en ny rad i tabellen.

Input som kommer gjennom kallet blir parset til et JSON-objekt og lastet inn i den nye raden i Dataverse tabellen.

Og da får vi masse deilige data!

Og vi liker masssse data!

Play? Develop? Discord.

Discord is a platform most known within the gaming community for its voice- and text-chat features. MaMNT needed a hip platform for collaboration up and running quickly during the initial stages of the day, and landed on using Discord with their pre-existing user profiles.

In order to avoid merge conflicts with three developers working in the same repo, a Discord bot was set up to post new commits as chat messages in a dedicated channel. This bot receives new commits via a GitHub webhook, enabling a trunc-based development cycle in MaMNT. All the hip, cool companies run trunc-based development, now including MaMNT!

MaMNT also avoids Teams like the plague, so Discord was immediately qualified as a collaboration solution simply by not being Teams.

Claimed badges:

Crawl, Mine & Process

We have created a scheduled flow that crawls through www.elskling.no results in my neighborhood electricity prices to get which provides that I could choose in my area.

  1. We created a custom connector, which gets data from www.elskling.no, so we could get this data using a Cloud Flow.
  2. Using this custom connector we were able to get all the providers of the zipCode we sent with the request.

3. After getting these data, we are able to add the Current Rate of each supplier to our Account record in Dataverse. By running this flow hourly, we are able to always get the latest price from each supplier.

Power Chess Final Delivery

Interessen rundt sjakk har eksplodert det siste året, blant annet The New York Times melder om rekordsalg og en økning på over 1000% på salg av fysiske sjakkbrett. Økningen i salget er hovedsakelig påvirket av den populære serien the Queen’s Gambit, og streaming programmet PogChamp. Men det er et problem, vi er midt i en pandemi og ingen kan spille fysisk sjakk mot hverandre.

Heldigvis sitter vi på løsningen: Power Chess!
Ved å bruke Power Chess kan du spille et fysisk sjakkparti mot hvem du vil uansett hvor i verden motstanderen befinner seg.

Slik fungerer det:

Hver spiller har hvert sitt sjakkbrett som er koblet på internett og bruker AI som identifiserer hvilke trekk som er utført. Når et sjakktrekk er identifisert vil sjakkbrettet til motstanderen utføre det samme sjakktrekket.

Under ser dere den automatiske lego-armen i Action. Filmen viser først et sjakktrekk på sjakkbrett 1, deretter ser vi lego-armen på sjakkbrett 2 på motstanderen sitt sjakkbrett.

Teknologien bak Power Chess

API og Azure Cognitive Services

Gjennom å integrere oss mot SharePoint, function app og ACS (Azure Cognitive Services)

I den tekniske løsningen vår benytter vi en integrasjon mot SharePoint, for å detektere at en ny fil har blitt lagt til, samt uthenting av denne filens innhold.

Videre har vi en integrasjon mot Function App som vi kjører et POST-kall mot tjenesten som gir oss 64 objekter tilbake.

Disse 64 objektene sendes til Azure Cognitive Services for analysering av innholdet.

Deretter blir dataen(Sjakkbrettet) prosessert og sendt til DataVerse ved en create.

Flow:

Ved å bruke Power Automate sin Cloud Flow har vi opprettet en Flow som trigges ved opprettelse av en ny fil i SharePoint i en mappe vi har kalt “Moves”. Ved å bruke en standard funksjon i Flow som henter innholdet i filen, får vi en string som vi kan sende til function app.

Function-app

Function appen mottar en string gjennom HTTP protokollen og deretter kutter opp bildet/Sjakkbrettet i 64 objekter, samt legger metadata på hver enkelt objekt for å identifisere hvor plasseringen er. Deretter blir disse sendt tilbake til flowen gjennom HTTP.

CRM / Dataverse

All dataen vi prosesserer illustrerer vi i en Model Driven app. Her kan vi se oversikt over alle rundene i enhvert spill, og posisjonene på alle brikkene. Ved hjelp av plattformen, og litt fancy HTML-kode, har vi fått denne skalerbar i forhold til enheter og skjermstørrelser.
Er man «on-the-run», kan man enkelt åpne applikasjonen via telefonen, og få en tilsvarende opplevelse.

HTML/CSS og Javascript kan være et kraftig verktøy. Om man trives i «den ville vesten», får man virkelig testet seg. Det har vært en god utfordring for oss CRM-konsulenter, men er fornøyd med resultatet.

Rasberry PI + Lego Boost

For å kontrollere Boost motoren til Lego har vi benyttet en Raspberry PI med Python script som kan sende signaler til boost motoren via BLE (Bluetooth Low Energy).

Badger vi clamer med denne posten:

#Glossy Pixels
#High 5
#Go With the Flow
#Chameleon
#Plug N’ Play
#Power User Love

Badge – Go with the flow

To manage the important task of notifying the crisis team when disaster occurs we have created a logic app that runs through a process.

IF the IOT device goes offline (LAVA killed the device) a notification is received to logic app. This in turn triggers a message in Teams of the Mayor, and rends the mayor an approval request for “Create Task Force”.

The logic app awaits the confirmation from the Mayor.

Once the Mayor confirms, we have a Disaster Team ready to coordinate the help we need, and a task to be completed.

IOT: Reading out messages on Sonos from Dataverse

When tasks are created in our nice little family the kids often doesn’t respond when their parents are sending out push notifications to their devices.

As a way to remind the kids on their tasks we have developed a system that reads out the tasks on the sonos speakers in the house

This setup requires the following components

  • Dataverse Tasks table
  • Power Automate Flow with “Common Data Service (current environment)” and “Service Bus” steps
  • Azure Service Bus
  • Talkity.com free text to speech subscription
  • Some device able to run Python on the same local netwok as the Sonos devices. E.g. a Raspberry PI
  • One or more Sonos Speakers

Power Automate Flow to put messages on Azure Service Bus Queue

Text to speech using Talkify

We have investigating several services for Text to Speech. Azure Cognitive Services have some, but we went the easy route and found one where it was possible to just compose a long url and post it directly and get a MP3 file with the speech back. https://talkify.com

The URL is on the format https://talkify.net/api/speech/v1?text=Clean your room&rate=2&format=mp3&voice=Microsoft Hazel Desktop&fallbackLanguage=English&key=xxxxxxx

The paid verison of Talkify also supports Norwegian, but as we are using the free version only English are supported

Our initial idea was to have a power automate flow step to do fetch the MP3 and upload the MP3 somewhere readable for Sonos (like Azure Blob Storage), but when it was as easy as calling an GET URL we can send that URL directly to Sonos.

Subscribing to the Azure Service Bus Queue and triggering the Sonos Speakers using Python running on a Raspberry PI

So playing files on the Sonos isn’t THAT difficult – especially when the sound files are from publically available URLs

The following Python script is using the SoCo Sonos Library (https://soco.readthedocs.io/en/v0.21/releases/0.13.html) and Azure Sevice Bus SDK v7.

The python script is deployed to a local raspberry Pi that can works as a local controller of the Sonos System.

Note: as long as you are on the same network as a Sonos speaker you can control it without any authentication. Tip for practical jokes 👌👍


from azure.servicebus import ServiceBusClient, ServiceBusMessage

from soco import SoCo
import soco
import urllib

sonos = SoCo('192.168.x.x') #kontor
print(sonos.player_name)

with ServiceBusClient.from_connection_string("Endpoint=sb://acdctaskservice.servicebus.windows.net/;SharedAccessKeyName=RootManageSharedAccessKey;SharedAccessKey=xxx=") as servicebus_client:
        print("ok")

        while True:
                try:
                        receiver = servicebus_client.get_queue_receiver(queue_name="taskqueue", max_wait_time=5)
                        with receiver:
                                for msg in receiver:
                                        print(msg)
                                        sonos.volume = 10
                                        url = "https://talkify.net/api/speech/v1?text="+ str(msg) +"&rate=2&format=mp3&voice=Microsoft Hazel Desktop&fallbackLanguage=English&key=xxx"
                                        print(url)
                                        sonos.play_uri(url)

                                        track = sonos.get_current_track_info()
                                        print(track)
                                        receiver.complete_message(msg)

                except Exception as e:
                        print( "Error: %s" % e )	
Bilderesultater for raspberry pi
Bilderesultater for sonos 1

Hopes for (some of) the following badges:

Embedding Numbnut

Go with the flow

Right now (uses service bus to send events directly)

Thieving Bastards (uses 3rd party SoCo Sonos library and shady text to speech service)

Nasty hacker (sends in the composed text-to-speech url with subscription key and everything to sonos)

And maybe a point or two in the categories

Blow my Mindstorm

Lego Autobots

Lego Shark Thank