Transportation
19 columns
120 rows
8 formats

Smart Parking Occupancy Tracking

This dataset provides detailed, timestamped occupancy records for smart parking facilities, including space-level usage, sensor status, pricing, and vehicle type. It enables facility managers and smart city planners to optimize operations, forecast demand, and analyze peak usage patterns for improved space allocation and dynamic pricing. The comprehensive structure supports both real-time monitoring and historical trend analysis.

last updated 17 Jan 2026
by GoMask

The brief that made it

Real-time monitoring of parking space availability

Sample rows

preview · 8 of 120 rows · all 19 columns

facility_idstring	occupancy_statusstring	pricing_rate_per_hourfloat	is_peak_hourboolean	address_citystring	facility_namestring	facility_typestring	address_streetstring	address_statestring	address_postal_codestring	address_countrystring	space_idstring	space_typestring	occupancy_start_timedatetime	occupancy_end_timedatetime	sensor_idstring	sensor_statusstring	occupancy_recorded_atdatetime	vehicle_typestring
FAC-001	occupied	5.25	true	San Francisco	Downtown Garage	garage	123 Market St	CA	94103	USA	S-001-101	regular	2024-06-01T09:15:00Z	blank	SENSOR-101	active	2024-06-01T09:15:05Z	car
FAC-002	vacant	0	false	Chicago	Westfield Lot	lot	456 Elm St	IL	60601	USA	S-002-204	accessible	blank	blank	SENSOR-204	active	2024-06-01T10:05:00Z	blank
FAC-003	occupied	8.5	true	Atlanta	Airport Parking Lot C	lot	789 Terminal Rd	GA	30337	USA	S-003-321	ev	2024-06-01T07:30:00Z	2024-06-01T08:45:00Z	SENSOR-321	active	2024-06-01T07:30:02Z	ev
FAC-004	vacant	1.25	false	Seattle	Uptown Street Parking	street	1010 Oak St	WA	98101	USA	S-004-105	other	blank	blank	blank	blank	2024-06-01T11:20:00Z	blank
FAC-005	reserved	0	false	New York	City Center Underground	underground	55 Pine Ave	NY	10007	USA	S-005-005	regular	blank	blank	SENSOR-005	inactive	2024-06-01T08:00:00Z	blank
FAC-006	occupied	7.75	true	Los Angeles	Eastside Garage	garage	200 Main St	CA	90012	USA	S-006-111	ev	2024-06-01T12:10:00Z	blank	SENSOR-111	active	2024-06-01T12:10:06Z	ev
FAC-007	reserved	0	false	Miami	Bayview Lot	lot	250 Bay Rd	FL	33131	USA	S-007-207	reserved	blank	blank	SENSOR-207	inactive	2024-06-01T09:45:00Z	blank
FAC-008	occupied	3.75	true	Sacramento	Capitol Garage	garage	1600 Capitol St	CA	95814	USA	S-008-014	accessible	2024-06-01T11:30:00Z	blank	SENSOR-014	active	2024-06-01T11:30:13Z	car
FAC-009	vacant	5	false	Memphis	Riverfront Lot	lot	310 River Rd	TN	38103	USA	S-009-019	ev	blank	blank	SENSOR-019	active	2024-06-01T10:55:00Z	blank
FAC-010	out_of_service	0	false	Denver	Central Street Parking	street	800 Center Ave	CO	80203	USA	S-010-201	other	blank	blank	blank	blank	2024-06-01T09:00:00Z	blank
FAC-011	occupied	6.5	true	Boston	Harbor Underground	underground	450 Harbor Blvd	MA	02110	USA	S-011-002	regular	2024-06-01T08:45:00Z	2024-06-01T10:00:00Z	SENSOR-002	active	2024-06-01T08:45:07Z	car
FAC-012	occupied	7.25	false	Dallas	Midtown Garage	garage	300 8th Ave	TX	75201	USA	S-012-112	ev	2024-06-01T13:10:00Z	blank	SENSOR-112	active	2024-06-01T13:10:03Z	ev
FAC-013	reserved	0	false	Minneapolis	North Lot	lot	401 Hill St	MN	55401	USA	S-013-013	accessible	blank	blank	SENSOR-013	inactive	2024-06-01T08:30:00Z	blank
FAC-014	vacant	0	false	Philadelphia	South Street Parking	street	900 South St	PA	19147	USA	S-014-312	accessible	blank	blank	blank	blank	2024-06-01T11:45:00Z	blank
FAC-015	occupied	4.35	true	Houston	Metro Garage	garage	200 Metro Ave	TX	77002	USA	S-015-020	regular	2024-06-01T14:00:00Z	blank	SENSOR-020	active	2024-06-01T14:00:04Z	car
FAC-016	vacant	2.5	false	Las Vegas	Grand Plaza Lot	lot	50 Grand Ave	NV	89101	USA	S-016-175	regular	blank	blank	SENSOR-175	active	2024-06-01T10:20:00Z	blank
FAC-017	out_of_service	0	false	Phoenix	Sunrise Underground	underground	111 Sunrise Blvd	AZ	85004	USA	S-017-004	ev	blank	blank	SENSOR-004	error	2024-06-01T07:10:00Z	blank
FAC-018	reserved	0	false	Detroit	Lakeside Lot	lot	500 Lake Dr	MI	48226	USA	S-018-208	reserved	blank	blank	SENSOR-208	inactive	2024-06-01T12:00:00Z	blank
FAC-019	occupied	8.25	true	Portland	Parkside Garage	garage	300 Parkside Ln	OR	97205	USA	S-019-015	ev	2024-06-01T15:15:00Z	blank	SENSOR-015	active	2024-06-01T15:15:07Z	ev
FAC-020	vacant	0	false	Columbus	Civic Center Lot	lot	700 Civic Center Dr	OH	43215	USA	S-020-307	accessible	blank	blank	SENSOR-307	active	2024-06-01T13:30:00Z	blank

What the 120 rows show

from the 120-row sample

Occupied (occupancy status) stands out: 43 of its 52 rows have is_peak_hour = true, against 0 of 68 for the rest.

36%is_peak_hour = true
2.5median pricing_rate_per_hour
2address countries
2vehicle types
3sensor statuses
4facility types

Is peak hour rate by occupancy_statusis_peak_hour = true

Occupied (occupancy status)'s mean pricing_rate_per_hour is 7.2, against 1.5 for vacant, 0.57 for reserved and 0.0 for out_of_service.

pricing_rate_per_hour120 rows, in bands of 5

Median 2.5, from 0.0 to 40.0.

address_city120 rows · top 10 of 37 values

Denver10
Seattle8
Dallas8
Boston7
Minneapolis7
San Diego6
New York5
Houston5
Las Vegas5
Columbus5

19 columns by typefrom the column list below

string 14
float 1
datetime 3
boolean 1

Columns

19 columns in four groups

blueprint · 19 columns
column	type	description	example
Text 14 columns
`facility_id`	string	Unique identifier for the smart parking facility	FAC-001
`facility_name`	string	Name of the parking facility	Downtown Garage
`facility_type`	string	Type of parking facility (e.g., garage, lot, street)garage · lot · street · underground · other	garage
`address_street`	string	Street address of the parking facility	123 Market St
`address_city`	string	City where the parking facility is located	San Francisco
`address_state`	string	State or region of the parking facility	CA
`address_postal_code`	string	Postal or ZIP code of the parking facility	94103
`address_country`	string	Country where the parking facility is located2 countries	USA
`space_id`	string	Unique identifier for the individual parking space	S-001-101
`space_type`	string	Type of parking space (e.g., regular, EV, accessible, reserved)regular · ev · accessible · reserved · other	regular
`occupancy_status`	string	Current occupancy status of the parking spaceoccupied · vacant · reserved · out_of_service	occupied
`sensor_id`	string	Unique identifier for the sensor monitoring the parking spaceoptional	SENSOR-101
`sensor_status`	string	Operational status of the sensor (active, inactive, error)active · inactive · error · optional	active
`vehicle_type`	string	Type of vehicle occupying the space if known (car, motorcycle, truck, EV, unknown)car · motorcycle · truck · ev · unknown · optional	car
Numbers 1 column
`pricing_rate_per_hour`	float	Current hourly rate for the parking space (if variable pricing applies)0 or more · optional	5.25
Dates and times 3 columns
`occupancy_start_time`	datetime	Timestamp when the parking space became occupiedoptional	2024-06-01T09:15:00Z
`occupancy_end_time`	datetime	Timestamp when the parking space became vacantoptional	2024-06-01T08:45:00Z
`occupancy_recorded_at`	datetime	Timestamp when the occupancy status was recorded	2024-06-01T09:15:05Z
True or false 1 column
`is_peak_hour`	boolean	Indicates if the occupancy event occurred during a defined peak houroptional	true

Use it for

A transportation dashboard
The is_peak_hour rate, pricing_rate_per_hour by occupancy_status and a breakdown of address_city. Excel, Power BI or Tableau.
Why do 43 of 120 rows have is_peak_hour = true?
A root-cause class exercise
Hand out the rows and one question. The answer is in the data, not in the brief.
Facilities120
FAC-0015.25occupied
FAC-0020vacant
FAC-0038.5occupied
A software demo
Believable facilities with facility_name, facility_type and address_street to fill a screen in front of a buyer.

This dataset120 rows19 columns

Yours1,000 rows19 columnsaddress_street: UK only

blueprint · smart-parking-occupancy-tracking

Behind this dataset

Same schema. As many rows as you need.

These 120 rows came out of a blueprint — 19 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Each row represents an hourly observation for a distinct sensor-enabled parking zone.
Occupancy value reflects the percentage of spaces occupied (0-100%) at the recorded hour.
Include sensor reliability status (active/fault/maintenance) for each observation.
Capture environmental factors: weather (clear, rain, snow), event proximity (yes/no), and local traffic congestion (low/medium/high).
Mark sensors reporting persistent faults (>2 hours) for maintenance flag.

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: smart-parking-occupancy-tracking

What should your data show?

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Sample rows

What the 120 rows show

Columns

Use it for

A transportation dashboard

A root-cause class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Transportation

What should your data show?