Real Time Location Insights (RTLI)

**Overview**
Provided by Virgin Media O2 Business, O2 Motion’s Real-Time Location Insights (RTLI) provides anonymised and aggregated mobility data derived from the UK’s largest mobile network. Using billions of daily network events, RTLI delivers near real-time insights into people movements and demographics, helping businesses, transport authorities, and urban planners make data-driven decisions. The data is processed with strict GDPR compliance and is available at high spatial granularity, including hexagonal grids (200m radius in cities) and ‘middle super output areas’, or MSOAs, Intermediate Zones in Scotland, and ‘super output areas’, or SOAs in Northern Ireland.
By leveraging RTLI, organisations gain an unrivalled and objective view of how populations move, dwell and interact with locations, enabling more effective strategic planning and operational responses.

**Use cases**
Event Management & Safety:

RTLI helps event organisers and public authorities monitor crowd movements before, during, and after large gatherings such as concerts, sporting events, and public celebrations. This enables improved crowd control, emergency response planning and post-event analysis.

Transport & Infrastructure Planning:

Transport operators and urban planners can use RTLI to analyse travel patterns, identify congestion points, and optimise infrastructure investments. The dataset supports decision making on public transport scheduling, road network improvements, and pedestrian flow management.

**Product details**
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*****rtli_hex_view***:** Aggregated and expanded counts of people by location and time interval
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**interval_datetime:** The interval the outputs relate to in datetime format YYYY-mm-dd HH:MM:SS

**interval_date:** The date of the interval in the format YYYY-mm-dd

**interval_time:** The time of the interval in the format HH:MM:SS

**interval_time_12hr:** The time of the interval in the format HH:MM:SS AM/PM

**hex:** The ID of the hex according to the Uber H3 index

**domestic_count:** The expanded count of domestic users in the hex for the interval

**international_visitor_count:** The expanded count of international visitors in the hex for the interval

**total_count:** The sum of the domestic_count and international_visitor_count

**male_domestic_count:** The expanded count of domestic male users

**female_domestic_count:** The expanded count of domestic female users

**age_1519_domestic_count:** The expanded count of domestic users aged 15 to 19

**age_2024_domestic_count:** The expanded count of domestic users aged 20 to 24

**age_2529_domestic_count:** The expanded count of domestic users aged 25 to 29

**age_3034_domestic_count:** The expanded count of domestic users aged 30 to 34

**age_3539_domestic_count:** The expanded count of domestic users aged 35 to 39

**age_4044_domestic_count:** The expanded count of domestic users aged 40 to 44

**age_4549_domestic_count:** The expanded count of domestic users aged 45 to 49

**age_5054_domestic_count:** The expanded count of domestic users aged 50 to 54

**age_5559_domestic_count:** The expanded count of domestic users aged 55 to 59

**age_6064_domestic_count:** The expanded count of domestic users aged 60 to 64

**age_6599_domestic_count:** The expanded count of domestic users aged 65 to 99

**seg_c2_domestic_count:** The expanded count of domestic users who have a social economic grade of C2

**seg_c1_domestic_count:** The expanded count of domestic users who have a social economic grade of C1

**seg_de_domestic_count:** The expanded count of domestic users who have a social economic grade of DE

**seg_ab_domestic_count:** The expanded count of domestic users who have a social economic grade of AB

**resident_domestic_count:** The expanded count of domestic users who are considered a resident in the hex

**worker_domestic_count:** The expanded count of domestic users who are considered a worker in the hex

**domestic_visitor_count:** The expanded count of domestic users who are considered a visitor in the hex

**lad_home_domestic_count:** The expanded breakdown of local authority districts relating to where domestic users are coming from

**lad_work_domestic_count:** The expanded breakdown of local authority districts relating to where domestic users work

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***lkp_hex_grid:*** A lookup table showing geographic information about each hex
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**hex:** The ID of the hex according to the Uber H3 index

**msoa:** The Middle layer Super Output Area (MSOA) id the hex is located in

**msoa_name:** msoa_name

**lad:** The Local authority district (LAD) id the hex is located in

**lad_name:** The name of the corresponding LAD

**region:** The region id the hex is located in

**region_name:** The region name the hex is located in

**country_name:** The country the hex is located in

**agg_geometry_wgs84_wkt:** The polygon of the hex when aggregating all the child resolution 9 hexes in wgs84 well known text format

**agg_geometry_wkt:** The polygon of the hex when aggregating all the child resolution 9 hexes in well known text format

**geometry_wgs84_wkt:** The polygon of the hex at its resolution in wgs84 well known text format

**geometry_wkt:** The polygon of the hex at its resolution in well known text format

**hex_res:** The resolution of the hex according to the h3 index

**is_active:** True if the hex is used in the current version of the hex grid

For more details, refer to the embedded notebook.

**Additional Insights**

- RTLI has been successfully used for major events, including the King’s Coronation and Queen’s Funeral, providing real-time crowd insights to government agencies.
- The dataset adheres to strict privacy and security standards, ensuring GDPR compliance and anonymisation.