Mesh API

🚧 Work in progress!

Contributing

Before committing code, please run yarn precommit to format your code and run the tests. Only commit your code when it's formatted and the tests pass. You can add it as a git precommit hook if you like.

Endpoints

https://api.nycmesh.net/v1/nodes
https://api.nycmesh.net/v1/links
https://api.nycmesh.net/v1/buildings
https://api.nycmesh.net/v1/members
https://api.nycmesh.net/v1/requests
https://api.nycmesh.net/v1/search
https://api.nycmesh.net/v1/los
https://api.nycmesh.net/v1/kml

Architecture

• Netlify Functions for hosting
• Express for handling requests
• PostgreSQL for main db
• PostGIS for line of sight db
• DigitalOcean Spaces (S3) for storing panorama images
• Auth0 for access control

Running locally

Clone the repo: git clone git@github.com:olivernyc/nycmesh-api.git
Install dependencies: yarn install
Run the local server: yarn start

You'll need a .env file with the following values:

DATABASE_URL=postgres://$user:$pass@$host:$port/$db
LOS_DATABASE_URL=postgres://$user:$pass@$host:$port/$db

S3_BUCKET=
S3_ENDPOINT=
S3_ID=
S3_KEY=

JWKS_URI=
JWT_AUDIENCE=
JWT_ISSUER=

SLACK_TOKEN=
SLACK_INSTALL_CHANNEL=
SLACK_PANO_CHANNEL=
SLACK_REQUEST_CHANNEL=

OSTICKET_API_KEY=

ACUITY_USER_ID=
ACUITY_API_KEY=

Schema

Currently, we use node numbers to represent join requests, members, and nodes. This schema is an attempt to detangle our data and create a common definition of the various components of the mesh.

Building

A physical location.

id	address	lat	lng	alt	bin	notes

Member

A person in the mesh community. For example, a node-owner, donor or installer.

id	name	email	phone

Node

A specific location on the network. Typically one per building.

id	lat	lng	alt	status	name	location

• id
• lat
• lng
• alt
• status (active, dead)
• name (optional) // e.g. "Saratoga", "SN1"
• location (optional) // Human readable location, e.g. "Roof", "Basement"
• notes (optional)
• create_date
• abandon_date (optional)
• building_id
• member_id

Join Request

• id
• date
• roof_access
• member_id
• building_id

Panorama

• id
• url
• date
• request_id

Device Type

• id
• name
• manufacturer
• range
• width

Device

A unit of hardware. Routers, radios, servers, etc.

• id
• status (in stock, active, dead)
• name (optional)
• ssid (optional)
• notes (optional)
• lat
• lng
• alt
• azimuth (direction in degrees, default 0)
• create_date
• abandon_date (optional)
• device_type_id
• node_id

Link

A connection between two devices. For example, an ethernet cable or wireless connection.

• id
• status (active, dead)
• create_date
• device_a_id
• device_b_id

Example Queries

Most join requests by member

SELECT
	COUNT(members.id) AS count,
	members.name AS member_name
FROM
	requests
	RIGHT JOIN members ON requests.member_id = members.id
GROUP BY
	members.id
ORDER BY
	count DESC;

Join requests in active node buildings

SELECT
	SUBSTRING(buildings.address, 1, 64) AS building_address,
	COUNT(DISTINCT requests.member_id) AS request_count,
	COUNT(DISTINCT nodes.member_id) AS node_count,
	JSON_AGG(DISTINCT nodes.id) AS node_ids,
	JSON_AGG(DISTINCT members.email) AS request_emails
FROM
	buildings
	JOIN requests ON buildings.id = requests.building_id
	JOIN members ON members.id = requests.member_id
	JOIN nodes ON buildings.id = nodes.building_id
WHERE
	nodes.status = 'active'
GROUP BY
	buildings.id
HAVING
	COUNT(DISTINCT requests.member_id) > COUNT(DISTINCT nodes.member_id)
ORDER BY
	request_count DESC

Tallest buildings with panos

SELECT
buildings.alt,
COUNT(DISTINCT requests.id) as request_count,
SUBSTRING(buildings.address, 1, 64) as building_address,
ARRAY_AGG(DISTINCT nodes.id) as node_ids,
ARRAY_AGG(DISTINCT panoramas.url) as pano_ids
FROM buildings
JOIN requests
ON buildings.id = requests.building_id
FULL JOIN nodes
ON buildings.id = nodes.building_id
JOIN panoramas
ON requests.id = panoramas.request_id
WHERE requests.roof_access IS TRUE
GROUP BY buildings.id
ORDER BY buildings.alt DESC;

Most join requests by building

SELECT
SUBSTRING(buildings.address, 1, 64) as building_address,
COUNT(buildings.id) as count
FROM requests
RIGHT JOIN buildings
ON requests.building_id = buildings.id
GROUP BY buildings.id
ORDER BY count DESC;

And node count

SELECT
buildings.alt as building_height,
-- COUNT(requests.id) as request_count,
COUNT(buildings.id) as node_count,
SUBSTRING (buildings.address, 1, 64) as building_address
FROM nodes
RIGHT JOIN buildings
ON nodes.building_id = buildings.id
RIGHT JOIN requests
ON nodes.building_id = requests.building_id
GROUP BY buildings.id
ORDER BY node_count DESC;

Node ids in building

SELECT array_agg(id) FROM nodes WHERE nodes.building_id = \$1;

Most nodes by building

SELECT
buildings.alt as building_height,
COUNT(buildings.id) as node_count,
SUBSTRING (buildings.address, 1, 64) as building_address
FROM nodes
RIGHT JOIN buildings
ON nodes.building_id = buildings.id
GROUP BY buildings.id
ORDER BY node_count DESC;

Nodes and join requests by building

SELECT
buildings.id,
COUNT(DISTINCT requests.id) as request_count,
COUNT(DISTINCT nodes.id) as node_count,
ARRAY_AGG(DISTINCT nodes.id) as node_ids,
SUBSTRING(buildings.address, 1, 64) as building_address
FROM buildings
JOIN requests
ON buildings.id = requests.building_id
JOIN nodes
ON buildings.id = nodes.building_id
GROUP BY buildings.id
ORDER BY request_count DESC;

Tallest buildings

SELECT
buildings.alt as building_height,
COUNT(nodes.id) as node_count,
SUBSTRING(buildings.address, 1, 64) as building_address
FROM nodes
RIGHT JOIN buildings
ON nodes.building_id = buildings.id
GROUP BY buildings.id
ORDER BY building_height DESC;

Tallest buildings with nodes

SELECT
buildings.id as building_id,
buildings.alt as building_height,
COUNT(nodes.id) as node_count,
array_agg(nodes.id) as node_ids,
SUBSTRING(buildings.address, 1, 64) as building_address
FROM buildings
LEFT JOIN nodes
ON buildings.id = nodes.building_id
GROUP BY buildings.id
-- HAVING COUNT(nodes.id) > 0 -- Toggle this line to hide/show nodeless buildings
ORDER BY building_height DESC;

Tallest buildings with join requests

SELECT
buildings.id as building_id,
buildings.alt as building_height,
COUNT(requests.id) as request_count,
array_agg(requests.id) as request_ids,
SUBSTRING(buildings.address, 1, 64) as building_address
FROM buildings
LEFT JOIN requests
ON buildings.id = requests.building_id
GROUP BY buildings.id
-- HAVING COUNT(nodes.id) > 0 -- Toggle this line to hide/show nodeless buildings
ORDER BY building_height DESC;

Line of Sight

DB Setup

Install lxml:

pip3 install lxml

Set up the db:

node scripts/reset-los-db.js

Download the building data:

curl -o building_data.zip http://maps.nyc.gov/download/3dmodel/DA_WISE_GML.zip
unzip building_data.zip -d building_data
rm building_data.zip

Insert the data

{
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA1_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA2_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA3_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA4_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA5_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA6_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA7_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA8_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA9_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA10_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA11_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA12_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA13_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA14_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA15_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA16_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA17_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA18_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA19_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA20_3D_Buildings_Merged.gml buildings
	python3 ./scripts/gml_to_pgsql.py ./building_data/DA_WISE_GMLs/DA21_3D_Buildings_Merged.gml buildings
} | psql $LOS_DATABASE_URL

Now we are ready to make queries!

Making Queries

Let's check for line of sight between Supernode 1 and Node 3.

Step 1: Look up BINs:

Use NYC GeoSearch or NYC Building Information Search.

Supernode 1 BIN: 1001389
Node 3 BIN: 1006184

Step 2: Get building midpoints:

SELECT ST_AsText(ST_Centroid((SELECT geom FROM ny WHERE bldg_bin = '1001389'))) as a,
ST_AsText(ST_Centroid((SELECT geom FROM ny WHERE bldg_bin = '1006184'))) as b;
#                     a                     |                    b
# ------------------------------------------+------------------------------------------
#  POINT(987642.232749068 203357.276907034) | POINT(983915.956115596 198271.837494287)
# (1 row)

Step 3: Get building heights:

SELECT ST_ZMax((SELECT geom FROM ny WHERE bldg_bin = '1001389')) as a,
ST_ZMax((SELECT geom FROM ny WHERE bldg_bin = '1006184')) as b;
#         a         |        b
# ------------------+------------------
#  582.247499999998 | 120.199699999997
# (1 row)

Step 4: Check for intersections:

SELECT a.bldg_bin
FROM ny AS a
WHERE ST_3DIntersects(a.geom, ST_SetSRID('LINESTRINGZ (983915 198271 582, 987642 203357 120)'::geometry, 2263));
#  bldg_bin
# ----------
# (0 rows)

There are no intersections. We have line of sight!