---
title: Nearby places for an agent
summary: A geo-aware memory tool that answers radius, nearest-k, map-box, and recent-visit questions over 80 remembered places.
level: Beginner
category: Geospatial
features: [point(), point.distance, point.withinBBox, POINT index, relationship property constraints]
browser: full
dataset: 80 places in Portland and Seattle and 18 visits by two agents (10 KB)
source: Synthetic, generated with a fixed seed by the examples project's 19-nearby-places/generate.py
license: Apache-2.0
---
# Nearby places for an agent
*A travel assistant remembers the places its users mention and the places its
agents visit. Five small queries turn that memory into tools: what is within
2 km, what is nearest, what is in this map box, and where an agent went
recently near here.*
The graph is `(:Place {name, kind, loc})-[:IN]->(:City)` for places, and
`(:Agent {id})-[:VISITED {ts, seq}]->(:Place)` for visits. `loc` is a WGS-84
point, so distances come back in metres. "Here" is Hotel Lucia in downtown
Portland.
```mermaid
flowchart LR
accTitle: Data model: agents visit places, and places are in cities
accDescr {
An Agent VISITED a Place, and each visit records a timestamp and a
sequence number. A Place has a name, a kind and a location, and is IN a
City.
}
Agent(("Agent
id")) -- "VISITED
ts · seq" --> Place(("Place
name · kind · loc"))
Place -- "IN" --> City(("City
name"))
class Agent l1
class Place l2
class City l3
```
## Load the places and visits
Constraints keep names unique, so `MERGE` never duplicates a place, city, or
agent. Visit timestamps are epoch milliseconds, and two relationship property
constraints reject a visit without an integer `ts`.
```cypher cell=schema setup
CREATE CONSTRAINT place_name IF NOT EXISTS FOR (p:Place) REQUIRE p.name IS UNIQUE;
CREATE CONSTRAINT city_name IF NOT EXISTS FOR (c:City) REQUIRE c.name IS UNIQUE;
CREATE CONSTRAINT agent_id IF NOT EXISTS FOR (a:Agent) REQUIRE a.id IS UNIQUE;
CREATE CONSTRAINT visit_ts IF NOT EXISTS
FOR ()-[r:VISITED]-() REQUIRE r.ts IS :: INTEGER;
CREATE CONSTRAINT visit_ts_nn IF NOT EXISTS
FOR ()-[r:VISITED]-() REQUIRE r.ts IS NOT NULL;
CREATE POINT INDEX place_loc IF NOT EXISTS FOR (p:Place) ON (p.loc)
```
```table
(no rows) · indexes added: 1, constraints added: 5
```
The fixture is one JSON file with a `places` list and a `visits` list.
`point({latitude, longitude})` builds a WGS-84 point (SRID 4326).
```cypher cell=load setup params=places
UNWIND $places AS r
MERGE (c:City {name: r.city})
CREATE (:Place {name: r.name, kind: r.kind,
loc: point({latitude: r.lat, longitude: r.lon})})-[:IN]->(c);
UNWIND $visits AS v
WITH DISTINCT v.agent AS id ORDER BY id
MERGE (:Agent {id: id});
UNWIND $visits AS v
MATCH (a:Agent {id: v.agent}), (p:Place {name: v.place})
CREATE (a)-[:VISITED {ts: v.ts, seq: v.seq}]->(p);
MATCH (p:Place) WITH count(p) AS places
MATCH (c:City) WITH places, count(c) AS cities
MATCH (:Agent)-[v:VISITED]->()
RETURN places, cities, count(v) AS visits
```
```table
| places | cities | visits |
|--------|--------|--------|
| 80 | 2 | 18 |
1 row · nodes created: 84, relationships created: 98, properties set: 280, labels added: 84
```
## Where is a place?
A point exposes its coordinates and reference system as properties. Return
scalars when a caller needs numbers; return the point itself when it will be
passed back into another query.
```json data=place
{
"name": "Blue Star Donuts"
}
```
```cypher cell=where params=place
MATCH (p:Place {name: $name})-[:IN]->(c:City)
RETURN p.name AS name, c.name AS city,
p.loc.latitude AS lat, p.loc.longitude AS lon, p.loc.srid AS srid,
valueType(p.loc) AS type
```
```table
| name | city | lat | lon | srid | type |
|--------------------|------------|---------|-----------|------|------------------|
| "Blue Star Donuts" | "Portland" | 45.5185 | -122.6795 | 4326 | "POINT NOT NULL" |
1 row
```
## Cafes within 2 km
`$here` is a plain map, so `point($here)` builds the caller's position. A
radius is a distance comparison rather than a function of its own:
`point.distance` returns the gap in metres, and `< $radius` keeps the places
inside it. Every radius query below is written the same way.
```json data=within
{
"here": {
"latitude": 45.5225,
"longitude": -122.68
},
"radius": 2000,
"kind": "cafe"
}
```
```cypher cell=within params=within
MATCH (p:Place)
WHERE p.kind = $kind AND point.distance(p.loc, point($here)) < $radius
RETURN p.name AS name, toInteger(round(point.distance(p.loc, point($here)))) AS metres
ORDER BY metres, name
```
```table
| name | metres |
|--------------------|--------|
| "Blue Star Donuts" | 447 |
| "Stumptown" | 507 |
| "Coava" | 1560 |
3 rows
```
The same radius, counted per city. Seattle is 230 km away and contributes
nothing:
```cypher cell=by-city params=within
MATCH (p:Place)-[:IN]->(c:City)
RETURN c.name AS city, count(p) AS places,
sum(CASE WHEN point.distance(p.loc, point($here)) < $radius
THEN 1 ELSE 0 END) AS within
ORDER BY city
```
```table
| city | places | within |
|------------|--------|--------|
| "Portland" | 55 | 13 |
| "Seattle" | 25 | 0 |
2 rows
```
## The radius on a plane
The explorer below draws the Portland bookstores on a plane around Hotel
Lucia and searches them with the radius tool. It takes the search in two
steps: one returns each bookstore's coordinates as numbers, and one is the
radius query with the position as `$lat` and `$lon` instead of the `$here`
map.
```cypher cell=bookstores
MATCH (p:Place {kind: 'bookstore'})-[:IN]->(:City {name: 'Portland'})
RETURN p.name AS name, p.kind AS kind,
p.loc.latitude AS latitude, p.loc.longitude AS longitude
ORDER BY name
```
```table
| name | kind | latitude | longitude |
|----------------------|-------------|----------|------------|
| "Belmont Bookstore" | "bookstore" | 45.52876 | -122.73347 |
| "Division Bookstore" | "bookstore" | 45.48139 | -122.67622 |
| "Marshall Bookstore" | "bookstore" | 45.51802 | -122.66999 |
| "Overton Bookstore" | "bookstore" | 45.55439 | -122.72204 |
| "Powell's" | "bookstore" | 45.5231 | -122.6813 |
| "Salmon Bookstore" | "bookstore" | 45.53677 | -122.66596 |
| "Yamhill Bookstore" | "bookstore" | 45.47985 | -122.73765 |
7 rows
```
```json data=near
{
"lat": 45.5225,
"lon": -122.68,
"radius": 2000
}
```
```cypher cell=near params=near
MATCH (p:Place {kind: 'bookstore'})
WITH p, point.distance(p.loc, point({latitude: $lat, longitude: $lon})) AS d
WHERE d < $radius
RETURN p.name AS name, round(d) AS metres
ORDER BY metres, name
```
```table
| name | metres |
|----------------------|--------|
| "Powell's" | 121.0 |
| "Marshall Bookstore" | 926.0 |
| "Salmon Bookstore" | 1929.0 |
3 rows
```
Dragging the circle runs the `near` step again with the circle's centre and
radius as its parameters; the arrow keys move the circle, and plus and minus
resize it. Each search runs under `PROFILE`, so the explorer also shows its
parse, plan and execute times and the database hits of its scan.
The `near` cell's recorded result: 3 places within 2000 m of latitude 45.5225, longitude -122.68.
| name | metres |
| --- | --- |
| Powell's | 121.0 |
| Marshall Bookstore | 926.0 |
| Salmon Bookstore | 1929.0 |
Live: the circle drags across the plane (arrow keys move it, plus and minus resize it), and each move runs the radius search again on the page's database in your browser with the circle as its parameters, lighting up the places it returns and showing the parse, plan and execute times and the scan's database hits; where the page has a box search, a box drags and searches the same way, and where it names its point index, a button creates or drops the index and searches again.
## The nearest k cafes
With no radius, order by distance and cut. `$k` is a parameter, so the tool
can ask for as many as it needs.
```json data=nearest
{
"here": {
"latitude": 45.5225,
"longitude": -122.68
},
"kind": "cafe",
"k": 2
}
```
```cypher cell=nearest params=nearest
MATCH (p:Place)
WHERE p.kind = $kind
WITH p, point.distance(p.loc, point($here)) AS d
ORDER BY d, p.name
LIMIT $k
RETURN p.name AS name, toInteger(round(d)) AS metres
```
```table
| name | metres |
|--------------------|--------|
| "Blue Star Donuts" | 447 |
| "Stumptown" | 507 |
2 rows
```
## What is in this map box?
`point.withinBBox(point, lowerLeft, upperRight)` answers "what is on screen".
The box below has Blue Star Donuts exactly on its lower-left corner and
Stumptown exactly on its upper-right corner. Both count: the boundary is
inclusive.
```json data=bbox
{
"ll": {
"latitude": 45.5185,
"longitude": -122.6795
},
"ur": {
"latitude": 45.5225,
"longitude": -122.6735
}
}
```
```cypher cell=bbox params=bbox
MATCH (p:Place)
WHERE point.withinBBox(p.loc, point($ll), point($ur))
WITH p ORDER BY p.name
RETURN count(p) AS in_box, collect(p.name) AS names
```
```table
| in_box | names |
|--------|-----------------------------------|
| 2 | ["Blue Star Donuts", "Stumptown"] |
1 row
```
## Where did this agent go recently, near here?
One agent's last visits within the radius. The anchor, `Agent {id: $agent}`,
is unique, and `ts` is an integer, so ordering by `v.ts` and cutting is
exact.
```json data=recent
{
"agent": "a1",
"here": {
"latitude": 45.5225,
"longitude": -122.68
},
"radius": 2000,
"n": 3
}
```
```cypher cell=recent params=recent
MATCH (a:Agent {id: $agent})-[v:VISITED]->(p:Place)
WHERE point.distance(p.loc, point($here)) < $radius
RETURN p.name AS name, v.seq AS seq, v.ts AS ts
ORDER BY v.ts DESC
LIMIT $n
```
```table
| name | seq | ts |
|--------------------|-----|---------------|
| "Blue Star Donuts" | 10 | 1788330030000 |
| "Stumptown" | 6 | 1788288080000 |
2 rows
```
## The latest visits across all agents
A supervisor wants the newest visits from every agent. The same read now
starts from two `Agent` nodes.
```json data=latest
{
"n": 3
}
```
```cypher cell=latest params=latest
MATCH (a:Agent)-[v:VISITED]->(p:Place)
RETURN a.id AS agent, p.name AS name, v.seq AS seq, v.ts AS ts
ORDER BY v.ts DESC, v.seq ASC
LIMIT $n
```
```table
| agent | name | seq | ts |
|-------|------------------|-----|---------------|
| "a2" | "Pike Place" | 6 | 1788363159000 |
| "a2" | "Pike Cafe" | 5 | 1788352372000 |
| "a2" | "Blanchard Cafe" | 4 | 1788350079000 |
3 rows
```
> **Note**
> Keep the second sort key (`v.seq ASC`) when the anchor pattern matches
> more than one node. Without it, Relate currently returns agent `a1`'s
> newest visits instead of the newest overall: it mis-orders a relationship
> property under `ORDER BY … LIMIT` when the pattern starts from more than
> one node.
To see the shape, return the visits themselves. Open the graph view:
```cypher cell=graph params=recent
MATCH path = (a:Agent)-[v:VISITED]->(p:Place)-[:IN]->(:City)
WHERE point.distance(p.loc, point($here)) < $radius
RETURN path
```
```gram
// 4 rows
(n82:Agent {id: "a1"})-[r89:VISITED {seq: 10, ts: 1788330030000}]->(n3:Place {kind: "cafe", loc: {crs: "wgs-84", latitude: 45.5185, longitude: -122.6795, srid: 4326}, name: "Blue Star Donuts"})-[r1:`IN`]->(n0:City {name: "Portland"})
(n82)-[r85:VISITED {seq: 6, ts: 1788288080000}]->(n4:Place {kind: "cafe", loc: {crs: "wgs-84", latitude: 45.5225, longitude: -122.6735, srid: 4326}, name: "Stumptown"})-[r2:`IN`]->(n0)
(n83:Agent {id: "a2"})-[r93:VISITED {seq: 2, ts: 1788281285000}]->(n5:Place {kind: "cafe", loc: {crs: "wgs-84", latitude: 45.5225, longitude: -122.66, srid: 4326}, name: "Coava"})-[r3:`IN`]->(n0)
(n83)-[r92:VISITED {seq: 1, ts: 1788254379000}]->(n6:Place {kind: "bookstore", loc: {crs: "wgs-84", latitude: 45.5231, longitude: -122.6813, srid: 4326}, name: "Powell's"})-[r4:`IN`]->(n0)
```
## Guard the caller's position
Nothing stops a caller from sending a cartesian point. Relate does not
reject a distance between points in different reference systems; it applies
the first argument's metric to both. Here the caller sent
`{"x": -122.68, "y": 45.5225}`:
```json data=guard
{
"here": {
"x": -122.68,
"y": 45.5225
},
"radius": 2000,
"kind": "cafe"
}
```
```cypher cell=mixed-crs params=guard
RETURN point($here).srid AS srid,
round(point.distance(point({latitude: 45.5225, longitude: -122.68}),
point($here)), 2) AS metres
```
```table
| srid | metres |
|------|--------|
| 7203 | null |
1 row
```
> **Note:** the distance is `null`, not a number: the two points carry
> different CRSs (WGS-84 vs cartesian), and Neo4j returns `null` for a
> mixed-CRS `point.distance` instead of computing across reference systems.
No error, and 0.0 metres: the cartesian `x`/`y` were read as
longitude/latitude. Had the caller swapped them, the answer would be a
plausible-looking wrong number instead. Check the SRID and the coordinate
ranges before the search runs. With the cartesian `$here` from the `guard`
parameters, the guarded tool returns no rows. Edit `here` to
`{"latitude": 45.5225, "longitude": -122.68}` and run it again:
```cypher cell=guarded params=guard
WITH point($here) AS here
WHERE here.srid = 4326
AND abs(here.latitude) <= 90 AND abs(here.longitude) <= 180
MATCH (p:Place)
WHERE p.kind = $kind AND point.distance(p.loc, here) < $radius
RETURN p.name AS name, toInteger(round(point.distance(p.loc, here))) AS metres
ORDER BY metres, name
```
```table
| name | metres |
|------|--------|
0 rows
```
## Data
The datasets the steps above load. Each block is a JSON object whose
keys are the query parameters.
places (10 KB)
```json data=places
{
"places": [
{"name": "Hotel Lucia", "kind": "hotel", "city": "Portland", "lat": 45.5225, "lon": -122.68},
{"name": "Blue Star Donuts", "kind": "cafe", "city": "Portland", "lat": 45.5185, "lon": -122.6795},
{"name": "Stumptown", "kind": "cafe", "city": "Portland", "lat": 45.5225, "lon": -122.6735},
{"name": "Coava", "kind": "cafe", "city": "Portland", "lat": 45.5225, "lon": -122.66},
{"name": "Powell's", "kind": "bookstore", "city": "Portland", "lat": 45.5231, "lon": -122.6813},
{"name": "Pike Place", "kind": "market", "city": "Seattle", "lat": 47.6097, "lon": -122.3422},
{"name": "Yamhill Cafe", "kind": "cafe", "city": "Portland", "lat": 45.55954, "lon": -122.7231},
{"name": "Irving Pharmacy", "kind": "pharmacy", "city": "Portland", "lat": 45.50472, "lon": -122.66591},
{"name": "Quimby Park", "kind": "park", "city": "Portland", "lat": 45.49611, "lon": -122.70354},
{"name": "Flanders Museum", "kind": "museum", "city": "Portland", "lat": 45.55345, "lon": -122.63174},
{"name": "Alder Market", "kind": "market", "city": "Portland", "lat": 45.52692, "lon": -122.71177},
{"name": "Division Bookstore", "kind": "bookstore", "city": "Portland", "lat": 45.48139, "lon": -122.67622},
{"name": "Yamhill Bookstore", "kind": "bookstore", "city": "Portland", "lat": 45.47985, "lon": -122.73765},
{"name": "Vaughn Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.55528, "lon": -122.67836},
{"name": "Overton Market", "kind": "market", "city": "Portland", "lat": 45.56149, "lon": -122.62327},
{"name": "Everett Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.54747, "lon": -122.65928},
{"name": "Salmon Park", "kind": "park", "city": "Portland", "lat": 45.51933, "lon": -122.66339},
{"name": "Alder Hotel", "kind": "hotel", "city": "Portland", "lat": 45.5657, "lon": -122.61317},
{"name": "Marshall Bookstore", "kind": "bookstore", "city": "Portland", "lat": 45.51802, "lon": -122.66999},
{"name": "Johnson Museum", "kind": "museum", "city": "Portland", "lat": 45.55963, "lon": -122.61875},
{"name": "Everett Cafe", "kind": "cafe", "city": "Portland", "lat": 45.47915, "lon": -122.67476},
{"name": "Clinton Hotel", "kind": "hotel", "city": "Portland", "lat": 45.53758, "lon": -122.64866},
{"name": "Lovejoy Park", "kind": "park", "city": "Portland", "lat": 45.49837, "lon": -122.68352},
{"name": "Kearney Park", "kind": "park", "city": "Portland", "lat": 45.51387, "lon": -122.69684},
{"name": "Burnside Cafe", "kind": "cafe", "city": "Portland", "lat": 45.49092, "lon": -122.64375},
{"name": "Clinton Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.5163, "lon": -122.67438},
{"name": "Taylor Hotel", "kind": "hotel", "city": "Portland", "lat": 45.56565, "lon": -122.71548},
{"name": "Burnside Market", "kind": "market", "city": "Portland", "lat": 45.47851, "lon": -122.71604},
{"name": "Kearney Market", "kind": "market", "city": "Portland", "lat": 45.55316, "lon": -122.71161},
{"name": "Alder Park", "kind": "park", "city": "Portland", "lat": 45.55781, "lon": -122.65309},
{"name": "Salmon Market", "kind": "market", "city": "Portland", "lat": 45.5629, "lon": -122.66027},
{"name": "Alder Cafe", "kind": "cafe", "city": "Portland", "lat": 45.54746, "lon": -122.64849},
{"name": "Burnside Pharmacy", "kind": "pharmacy", "city": "Portland", "lat": 45.48971, "lon": -122.66668},
{"name": "Hawthorne Park", "kind": "park", "city": "Portland", "lat": 45.55042, "lon": -122.62751},
{"name": "Lovejoy Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.56357, "lon": -122.61796},
{"name": "Couch Pharmacy", "kind": "pharmacy", "city": "Portland", "lat": 45.47392, "lon": -122.62056},
{"name": "Thurman Hotel", "kind": "hotel", "city": "Portland", "lat": 45.50793, "lon": -122.6946},
{"name": "Davis Museum", "kind": "museum", "city": "Portland", "lat": 45.51452, "lon": -122.62215},
{"name": "Salmon Bookstore", "kind": "bookstore", "city": "Portland", "lat": 45.53677, "lon": -122.66596},
{"name": "Quimby Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.47408, "lon": -122.68934},
{"name": "Belmont Museum", "kind": "museum", "city": "Portland", "lat": 45.49958, "lon": -122.7016},
{"name": "Belmont Bookstore", "kind": "bookstore", "city": "Portland", "lat": 45.52876, "lon": -122.73347},
{"name": "Flanders Cafe", "kind": "cafe", "city": "Portland", "lat": 45.48912, "lon": -122.70503},
{"name": "Overton Bookstore", "kind": "bookstore", "city": "Portland", "lat": 45.55439, "lon": -122.72204},
{"name": "Glisan Hotel", "kind": "hotel", "city": "Portland", "lat": 45.52472, "lon": -122.65898},
{"name": "Upshur Museum", "kind": "museum", "city": "Portland", "lat": 45.54853, "lon": -122.64524},
{"name": "Couch Market", "kind": "market", "city": "Portland", "lat": 45.50464, "lon": -122.61045},
{"name": "Northrup Pharmacy", "kind": "pharmacy", "city": "Portland", "lat": 45.51475, "lon": -122.69744},
{"name": "Couch Hotel", "kind": "hotel", "city": "Portland", "lat": 45.50866, "lon": -122.70067},
{"name": "Kearney Museum", "kind": "museum", "city": "Portland", "lat": 45.47497, "lon": -122.68041},
{"name": "Taylor Pharmacy", "kind": "pharmacy", "city": "Portland", "lat": 45.50094, "lon": -122.70588},
{"name": "Johnson Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.5334, "lon": -122.64365},
{"name": "Burnside Hotel", "kind": "hotel", "city": "Portland", "lat": 45.49792, "lon": -122.68376},
{"name": "Flanders Restaurant", "kind": "restaurant", "city": "Portland", "lat": 45.56668, "lon": -122.68074},
{"name": "Couch Cafe", "kind": "cafe", "city": "Portland", "lat": 45.47951, "lon": -122.68022},
{"name": "Everett Museum", "kind": "museum", "city": "Portland", "lat": 45.50086, "lon": -122.63163},
{"name": "Pike Market", "kind": "market", "city": "Seattle", "lat": 47.58972, "lon": -122.37561},
{"name": "Cherry Bookstore", "kind": "bookstore", "city": "Seattle", "lat": 47.61666, "lon": -122.29283},
{"name": "Blanchard Bookstore", "kind": "bookstore", "city": "Seattle", "lat": 47.61048, "lon": -122.33574},
{"name": "Madison Museum", "kind": "museum", "city": "Seattle", "lat": 47.6025, "lon": -122.36664},
{"name": "Pike Cafe", "kind": "cafe", "city": "Seattle", "lat": 47.60903, "lon": -122.36381},
{"name": "Columbia Museum", "kind": "museum", "city": "Seattle", "lat": 47.60816, "lon": -122.3155},
{"name": "Pine Hotel", "kind": "hotel", "city": "Seattle", "lat": 47.62318, "lon": -122.32256},
{"name": "Pike Pharmacy", "kind": "pharmacy", "city": "Seattle", "lat": 47.62768, "lon": -122.35556},
{"name": "Madison Restaurant", "kind": "restaurant", "city": "Seattle", "lat": 47.58144, "lon": -122.33158},
{"name": "Pike Bookstore", "kind": "bookstore", "city": "Seattle", "lat": 47.65943, "lon": -122.3091},
{"name": "Stewart Pharmacy", "kind": "pharmacy", "city": "Seattle", "lat": 47.6279, "lon": -122.36409},
{"name": "Stewart Park", "kind": "park", "city": "Seattle", "lat": 47.61066, "lon": -122.31556},
{"name": "Lenora Bookstore", "kind": "bookstore", "city": "Seattle", "lat": 47.6549, "lon": -122.35739},
{"name": "Seneca Restaurant", "kind": "restaurant", "city": "Seattle", "lat": 47.62295, "lon": -122.29118},
{"name": "Blanchard Cafe", "kind": "cafe", "city": "Seattle", "lat": 47.65724, "lon": -122.318},
{"name": "Blanchard Market", "kind": "market", "city": "Seattle", "lat": 47.63592, "lon": -122.33786},
{"name": "Virginia Bookstore", "kind": "bookstore", "city": "Seattle", "lat": 47.63039, "lon": -122.33496},
{"name": "Yesler Hotel", "kind": "hotel", "city": "Seattle", "lat": 47.60041, "lon": -122.30023},
{"name": "Bell Market", "kind": "market", "city": "Seattle", "lat": 47.64225, "lon": -122.29814},
{"name": "Lenora Restaurant", "kind": "restaurant", "city": "Seattle", "lat": 47.62588, "lon": -122.37153},
{"name": "Blanchard Park", "kind": "park", "city": "Seattle", "lat": 47.64802, "lon": -122.29406},
{"name": "Union Restaurant", "kind": "restaurant", "city": "Seattle", "lat": 47.58381, "lon": -122.31199},
{"name": "Seneca Pharmacy", "kind": "pharmacy", "city": "Seattle", "lat": 47.65149, "lon": -122.3714},
{"name": "Pike Hotel", "kind": "hotel", "city": "Seattle", "lat": 47.59158, "lon": -122.33062}
],
"visits": [
{"agent": "a1", "place": "Alder Hotel", "ts": 1788251014000, "seq": 1},
{"agent": "a1", "place": "Lovejoy Restaurant", "ts": 1788256140000, "seq": 2},
{"agent": "a1", "place": "Clinton Hotel", "ts": 1788262124000, "seq": 3},
{"agent": "a1", "place": "Flanders Museum", "ts": 1788264540000, "seq": 4},
{"agent": "a1", "place": "Overton Bookstore", "ts": 1788271493000, "seq": 5},
{"agent": "a1", "place": "Stumptown", "ts": 1788288080000, "seq": 6},
{"agent": "a1", "place": "Kearney Museum", "ts": 1788297186000, "seq": 7},
{"agent": "a1", "place": "Burnside Pharmacy", "ts": 1788304446000, "seq": 8},
{"agent": "a1", "place": "Everett Cafe", "ts": 1788322173000, "seq": 9},
{"agent": "a1", "place": "Blue Star Donuts", "ts": 1788330030000, "seq": 10},
{"agent": "a1", "place": "Cherry Bookstore", "ts": 1788338666000, "seq": 11},
{"agent": "a1", "place": "Madison Restaurant", "ts": 1788347754000, "seq": 12},
{"agent": "a2", "place": "Powell's", "ts": 1788254379000, "seq": 1},
{"agent": "a2", "place": "Coava", "ts": 1788281285000, "seq": 2},
{"agent": "a2", "place": "Yamhill Cafe", "ts": 1788314362000, "seq": 3},
{"agent": "a2", "place": "Blanchard Cafe", "ts": 1788350079000, "seq": 4},
{"agent": "a2", "place": "Pike Cafe", "ts": 1788352372000, "seq": 5},
{"agent": "a2", "place": "Pike Place", "ts": 1788363159000, "seq": 6}
]
}
```