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action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /var/www/rahi_io/wp-includes/functions.php on line 6114Organizations need to understand how many people are using common areas, conference rooms, workspaces and other parts of the office environment. The objective is to control the number of people who occupy small spaces and determine how to best configure the environment to support hybrid work models.
Many organizations are opting to eliminate large conference rooms and meeting spaces in favor of smaller meeting and huddle rooms. Some are also looking to reduce or even eliminate assigned workspaces, adopting a “hotel” model in which employees use any available workspaces when they are in the office.
Rahi has partnered with Xovis and Density to develop workplace analysis solutions for customers. The technology developed by Xovis and Density allows for office personnel entering into or out of a building, floor or workspace to be counted. This allows queue detection and physical distancing management so that customers have the data they need for effective facilities design and management.
Xovis ceiling-mounted sensors have two wide-angle lenses for “stereo” vision. Each lens captures the scene from different perspectives, and the sensor analyzes each pixel to calculate the optical disparity up to 30 times per second. The result is a precise 3-D image of the scene that enables accurate people counting. The raw data never leaves the sensor — artificial intelligence processes the data so that people can be counted without compromising security.
Density’s Open Area sensors provide an almost 360-degree view of space utilization, down to the square foot, for tracking the utilization of desks, conference rooms and open spaces. The company’s Entry sensors count people entering and leaving doorways, floors and rooms. Density also offers a portfolio of software tools for managing desk configurations, assigning amenities, providing real-time occupancy data, space utilization, and desk booking.
As with any Internet of Things (IoT) project, the installation of workplace analysis sensors requires proper planning. How many sensors are needed? Where will they be placed? How will they be connected to the network?
The Rahi team starts with basic floor plan information to estimate the number of sensors based on the areas the customer wants to monitor. From there, a site walkthrough is scheduled and we take accurate measurements from floor to ceiling, including openings and doorways. Our installation experts take pictures to understand where there might be any kind of obstacle, such as exit signs, large light fixtures or HVAC equipment.
Rahi then install the sensors to cover the desired area. The sensors use ‘Power over Ethernet’, so only low-voltage wiring is required. Rahi’s Service team also installs cabling if the customer does not have a preferred cabling provider.
The data collected by the sensors is correlated in a dashboard that can be utilized in multiple ways. Facilities managers can use the data to optimize the design and layout of the space. Organizations that move to a “hotel” model can also install displays that show the available workspaces. When employees enter the front office or lobby area, they can see red lights for occupied spaces and green lights for those that are available. When someone moves into a workspace, the light changes color.
Some platforms give customers the ability to set occupancy thresholds for spaces. For example, if the occupancy level is 12 and 10 people enter the space, the display will change color to indicate the space is nearing capacity.
The Rahi team has completed large-scale workspace analysis projects across facilities worldwide. We have the expertise, experience, partnerships and global reach to help organizations optimize the safety, convenience and cost-efficiency of their post-pandemic work environments.
Let our experts design, develop, deploy and manage your requirements while you focus on what's important for your business