Network Data Occupancy Tracking for Dynamic Workspaces
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Solution Overview
Problem
Existing methods for determining physical real estate utilization, such as low-technology people counting and sensor-based systems, face challenges in accurately accounting for varying types of users and their usage patterns, particularly in modern work environments with trends like desk-sharing and remote work.
Innovation Solution
Utilizing network and security data, including Internet Protocol (IP) addresses and user identifiers, to identify signs of work and determine user characteristics and physical locations, thereby generating insights on physical real estate utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If low-technology methods like counting people are used, then implementation is simple, but accuracy is poor due to double-counting and failure to account for partial-day usage
Solution Approach 1:
The patent replaces manual counting methods with automated network data analysis. Instead of physically counting people, the system uses IP address and user identifier data from existing network infrastructure to automatically track occupancy, eliminating human error while maintaining implementation simplicity through software-based solutions.
Solution Approach 2:
The patent introduces network data (IP addresses, user identifiers) as an intermediary to bridge the gap between simple counting and accurate tracking. This intermediary data layer enables automatic identification of unique individuals and their presence duration without requiring complex sensor systems or manual intervention.
2Measurement precision
If sensor-based systems are used, then measurement precision improves, but device complexity increases and different user types are not distinguished
Solution Approach 1:
The patent makes the existing network infrastructure multi-functional by using it not only for its original purpose but also for occupancy tracking. The same network data that routes communications now also identifies user presence and characteristics, eliminating the need for separate sensor systems and reducing overall device complexity.
Solution Approach 2:
The system uses the network's own data to perform occupancy tracking without requiring external sensors or additional infrastructure. The network essentially serves itself by providing both communication functionality and occupancy measurement through its existing data streams of IP addresses and user identifiers.
3Ease of operation
If traditional occupancy methods are used, then implementation is straightforward, but adaptability to modern work environments like desk-sharing and teleworking is poor
Solution Approach 1:
The patent implements a dynamic occupancy tracking system that adapts to changing work patterns. Instead of static assumptions about desk assignments, the system continuously monitors network data to detect when employees are present, absent, or working remotely, automatically adjusting occupancy measurements to reflect current work arrangements like desk-sharing and teleworking.
Solution Approach 2:
The system changes the parameters used for occupancy measurement from fixed physical presence to flexible network-based identification. By using IP addresses and user identifiers that can exist regardless of physical location, the system adapts to various work arrangements while maintaining straightforward implementation through automated data collection and analysis.
Data Source
AI summary
A method of determining physical real estate utilization can begin with receiving network and security data of an enterprise. A sign of work can be identified from the network and security data. For each sign of work, an Internet Protocol (IP) address and user identifier can be determined from the network and security data associated with the sign of work. Further, one or more user characteristics associated with the user identifier can be determined, and a physical location of the user at a time can be determined based on the IP address. The user characteristics and the physical location can be stored. Insights on physical real estate utilization can be generated based on at least two of: user characteristics of each user, the physical location of each user, and temporal data from the received network and security data, and a set of the insights can be output.