17871543. ESTIMATING A NUMBER OF PEOPLE AT A POINT OF INTEREST USING VEHICLE SENSOR DATA AND GENERATING RELATED VISUAL INDICATIONS simplified abstract (Microsoft Technology Licensing, LLC)
Contents
- 1 ESTIMATING A NUMBER OF PEOPLE AT A POINT OF INTEREST USING VEHICLE SENSOR DATA AND GENERATING RELATED VISUAL INDICATIONS
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 ESTIMATING A NUMBER OF PEOPLE AT A POINT OF INTEREST USING VEHICLE SENSOR DATA AND GENERATING RELATED VISUAL INDICATIONS - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Original Abstract Submitted
ESTIMATING A NUMBER OF PEOPLE AT A POINT OF INTEREST USING VEHICLE SENSOR DATA AND GENERATING RELATED VISUAL INDICATIONS
Organization Name
Microsoft Technology Licensing, LLC
Inventor(s)
Leon Oliver Stenneth of Chicago IL (US)
Catalin Bogdan Capota of Chicago IL (US)
ESTIMATING A NUMBER OF PEOPLE AT A POINT OF INTEREST USING VEHICLE SENSOR DATA AND GENERATING RELATED VISUAL INDICATIONS - A simplified explanation of the abstract
This abstract first appeared for US patent application 17871543 titled 'ESTIMATING A NUMBER OF PEOPLE AT A POINT OF INTEREST USING VEHICLE SENSOR DATA AND GENERATING RELATED VISUAL INDICATIONS
Simplified Explanation
Methods and systems have been developed to estimate the number of people at a specific location using vehicle data. This involves receiving data from multiple vehicles within a geographic boundary that includes the location of interest. From this data, information from door sensors is extracted. Using this subset of data, an estimated count of people within the geographic boundary during a specified time period is determined. An indication of the estimated number of people is then generated.
- Vehicle data is collected from multiple vehicles within a specific geographic area.
- Data from door sensors in the vehicles is extracted.
- The extracted data is used to estimate the number of people within the geographic area during a specified time period.
- An indication of the estimated number of people is generated.
Potential Applications
- Crowd management: This technology can be used to estimate the number of people at events, public spaces, or tourist attractions, helping authorities manage crowd control and ensure safety.
- Urban planning: By estimating the number of people in different areas at different times, city planners can make informed decisions about infrastructure development, transportation systems, and resource allocation.
- Retail analytics: Retailers can use this technology to estimate foot traffic and customer flow in their stores, helping them optimize store layouts, staffing, and inventory management.
Problems Solved
- Accurate estimation: This technology provides a method to estimate the number of people at a specific location without relying on manual counting or surveys, which can be time-consuming and prone to errors.
- Real-time monitoring: By using vehicle data, the estimation can be done in real-time, allowing for immediate response and decision-making.
- Scalability: The use of vehicle data allows for scalability, as it can cover large geographic areas and handle a high volume of data.
Benefits
- Efficiency: The automated estimation process saves time and resources compared to manual counting methods.
- Accuracy: By utilizing vehicle data and door sensor information, the estimation can provide a more accurate count of people at a location.
- Real-time insights: The ability to estimate the number of people in real-time enables timely decision-making and response to changing situations.
Original Abstract Submitted
Methods and systems for estimating a number of people at a point of interest using vehicle data are provided. In some examples, vehicle data is received, from a plurality of vehicles, that corresponds to a geographic boundary encompassing a point of interest. From the vehicle data, a first subset of data corresponding to door sensor information is extracted. Based on the first subset of data, an estimated number of people within the geographic boundary, during a specified period of time, is determined. An indication corresponding to the estimated number of people within the geographic boundary is generated.
