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https://github.com/iteam1337/predictivemovement
Predictive Movement
https://github.com/iteam1337/predictivemovement
Last synced: about 5 hours ago
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Predictive Movement
- Host: GitHub
- URL: https://github.com/iteam1337/predictivemovement
- Owner: Iteam1337
- Created: 2019-07-05T14:08:14.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2021-09-27T14:48:43.000Z (about 3 years ago)
- Last Synced: 2024-04-14T11:04:23.798Z (7 months ago)
- Language: HTML
- Homepage: https://predictivemovement.se
- Size: 7.87 MB
- Stars: 4
- Watchers: 5
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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README
# Predictive Movement
[](https://github.com/iteam1337/predictivemovement/actions)
This is the source code for the collaborative open source project Predictive Movement.
## About
Predictive Movement aims to create a digital platform that will act as a collaborative hub for the transports of people and goods with the help of artificial intelligence (AI). In its first phase, the project will solve the societal challenge of parcel deliveries in rural areas. Further on, the project aims to deal with optimizing availability and accessibility in areas ranging from urban to rural.
Predictive Movement is a project financed by, among others, Sweden’s Innovation Agency (Vinnova) and the Swedish Transport Administration. The project includes one Swedish region, four municipalities, a university, authorities as well as key actors within digitization and traffic/logistics. An important driving force behind the project is to combat climate change and to reduce emissions caused by road transports.
## Navigating the code
The source code for the project is contained in this mono-repo. Within the [packages](packages) folder you will find all included packages. Here is a summary of the components:
- [Engine](packages/engine_umbrella/apps/engine) The main logic written in Elixir
- [Driver interface](packages/driver-interface) Bot in Telegram for communicating with drivers
- [Booking interface](packages/booking-interface) Bot in Telegram for communicating with bookers of transport
- [Engine UI](packages/engine-ui) Main UI for visualising current bookings and cars
- [Engine Server](packages/engine-server) Node-server backend for Engine UI
- [Route Optimization Jsprit](packages/route-optimization-jsprit) A fork of [Jsprit](https://github.com/graphhopper/jsprit); used to help calculating the best vehicle to booking matches.
- [Vehicle Offer](packages/vehicle-offer) Re-routes vehicle offers to the queue
- [Auto Accept Offer](packages/auto-accept-offer) Auto accepts offers for vehicles created in the Engine UI
- [Booking-dispatcher](packages/booking-dispatcher) Auto accepts offers for vehicles created in the Engine UI
- [Signing UI](packages/signing-ui) UI for signing a package on delivery
## Running the project
### Using kubernetes
#### Secrets
The following kubernetes secrets are used:
DRIVER_TOKEN - Driver Telegram bot token. Used by driver-interace
GOOGLE_TOKEN - Used by driver-interace
POSTNORD_KEY - Used by engine-server to get information from Postnord API
MINIO_ROOT_PASSWORD - Used by minio and engine-server
POSTGRES_PASSWORD - Used by postgres, engine and postgres-backup
#### Deployment
To deploy the dependencies of the stack (usually done once and it's DBs) to your Kubernetes cluster, use Skaffold:
skaffold -f skaffold-dependencies.yaml run
To deploy the relevant packages to your Kubernetes cluster, use Skaffold:
skaffold run --tail
To debug run:
skaffold dev
#### Before you start running the project
Start by exporting port 9200
```
kubectl port-forward elasticsearch-0 9200:9200 --namespace pelias
```
### Running Predictive Movement locally
You will need the following API keys
POSTNORD_KEY - for engine-server
REACT_APP_MAPBOX_ACCESS_TOKEN - for engine-ui
GOOGLE_API_TOKEN - for driver-interface
TELEGRAM_BOT_TOKEN - for driver-interface
#### Set environment variables
create .env-file in packages/driver-interface/.env with
GOOGLE_API_TOKEN=
BOT_TOKEN= / or create your own bot in telegram
create .env-file in packages/engine-ui/.env with
REACT_APP_MAPBOX_ACCESS_TOKEN=
#### Start the services
docker-compose up
#### Run migrations and start the engine
cd packages/engine_umbrella/
mix deps.get
mix setup_dev
iex -S mix
#### Running tests
Make sure you've started the dependencies with docker-compose up -d then run
cd packages/engine_umbrella/
mix deps.get
mix setupTestDatabase
mix test
### Helper/utility functions for populating the state
The umbrella project has an application "message_generator" which is used to create rabbitMQ messages for producing transports and bookings. First start the umbrella project in an elixir shell
cd packages/engine_umbrella/
iex -S mix
Then the Generator module is available inside the shell.
add_booking/0 add_booking/1 add_transport/0 add_transport/1
The argument can be a map containing properties or an atom for creating a generic one close to a city, (`:stockholm`, `:gothenburg`, `:ljusdal`)
or in the case of the add_transport; a keyword list can also be used containing `:phone`, i.e: `Generator.add_transport(phone: "0735333")`
**Design mockup:** [Figma](https://www.figma.com/file/DdBjpoKd0T9OkWmhlpd48Nfa/Predictive-Movement)
---
## Release
You will need:
- [docker installed](https://docs.docker.com/engine/install/)
- [kubectl installed](https://kubernetes.io/docs/tasks/tools/install-kubectl/)
- [skaffold installed](https://skaffold.dev/docs/install/)
- [kustomize installed](https://kubernetes-sigs.github.io/kustomize/installation/)
- login with your Docker account
- access to Iteam Kubernetes cluster
- mapbox access token from `Predictivemovement` LastPass folder
To deploy the dependencies of the stack (usually done once and it's DBs) to your Kubernetes cluster, use Skaffold:
skaffold -f skaffold-dependencies.yaml run --profile prod
Set environment variables that are used by Docker at build time (for the UI) and run the skaffold command with a profile:
```sh
export REACT_APP_MAPBOX_ACCESS_TOKEN=
export REACT_APP_ENGINE_SERVER=https://engine-server.iteamdev.io
skaffold run --profile prod
```
---
## Data backups
We use [postgres-backup](https://github.com/alexanderczigler/docker/tree/master/postgres-backup)
To restore a backup exec into the `postgres-backup` pod
```bash
kubectl exec -it postgres-backup /bin/bash
/restore.sh /backup/latest.psql.gz # or choose a different backup you want
```
---
## Vocabulary
```
Transport (previously vehicle){
id
busy
activities
booking_ids
metadata
start_address
end_address
earliest_start
latest_end
profile
capacity
}
```
```
Booking {
id
pickup
delivery
assigned_to
external_id
events
metadata
size
requires_transport_id
}
```
Plan
Route