With a possible infection, it's crucial to list the affected people in the organization as soon as possible and check their seating location to find out who else might be infected.
We released a special report in SAM, the Neighborhood report which allows you to filter by name and time period and it shows the employee's neighborhood in the office area.
With this report, you can identify the affected people in the organization as soon as possible and check their seating location to find out who else might be infected. The system generates a list weighted by the distance between the employees indicating how frequently the employees booked a desk in the infected person's neighborhood.
We also added an algorithm to the system which automatically books every second seat (or more based on the user's preferences) in order to ensure social distance and minimize the physical contact between colleagues.
These tools help analyze how building and office spaces are utilized. The sensors could monitor different areas within the office: the workstations, meeting rooms, or even the parking lots.
The sensors detect parking vehicles, then set the status to occupied or unoccupied. The status information is communicated through a radio connection to the hub. The hub collects this information from multiple sensors and transmits it to the cloud through the Ethernet network.
The sensors are so small, that could be discretely placed on the floor of the parking lot and not disruptive to employees. In addition, they are resistant to mechanical impact.
As the sensors are wireless, the installation and maintenance costs are minimal. The client can decide whether they want to apply the sensors temporarily or permanently.
During the parking booking no personal information is captured, simply illustrate the utilization, while GDPR requirements is guaranteed.
They are optimized for low power consumption, each sensor has a built-in battery (battery life up to 10 years).
SAM gets the data through an API and visualizes them on the floor plan. Parking information is stored in the cloud (Amazon Web Services) , therefore always up-to-date. Occupancy data can be tracked in real-time or can be downloaded for the past.