{"id":15346,"date":"2024-07-18T09:00:55","date_gmt":"2024-07-18T16:00:55","guid":{"rendered":"https:\/\/www.microsoft.com\/insidetrack\/blog\/?p=15346"},"modified":"2024-07-24T11:47:25","modified_gmt":"2024-07-24T18:47:25","slug":"enhancing-space-management-internally-at-microsoft-with-wi-fi-data","status":"publish","type":"post","link":"https:\/\/www.microsoft.com\/insidetrack\/blog\/enhancing-space-management-internally-at-microsoft-with-wi-fi-data\/","title":{"rendered":"Enhancing space management internally at Microsoft with Wi-Fi data"},"content":{"rendered":"

\"Microsoft
\nSpace management and employee engagement are two critical aspects of any modern workplace, including internally here at Microsoft.<\/p>\n

Figuring out how to get both right leads to important questions:<\/p>\n

How can organizations understand the best use of their building spaces, including offices and common spaces, while providing better experiences for their employees? How can they reduce the cost and complexity of installing and maintaining IoT sensors to measure people density in different areas? How can they protect the privacy of employees and their devices and comply with privacy regulations?<\/p>\n

This is what we asked ourselves when we set out to enhance both space utilization and the experience our employees have when they go into the office in our brand-new buildings here at Microsoft headquarters in Redmond, Washington.<\/p>\n

We in Microsoft Digital, the company\u2019s IT organization, knew that each new building would come with a wireless access point (WAP) system that employees use to access Wi-Fi. We knew the data from the access points could be used to measure the people density in different areas. The question was, how could we use this data to provide real-time insights to employees and facility managers privately and securely?<\/p>\n

We identified an opportunity to reuse the existing devices and the data that we already had from these devices. It was a cost-optimized way of handling our requirements.<\/p>\n

\u2014 Nritya Reddy, senior product manager, Microsoft Digital<\/p>\n<\/blockquote>\n

Using WAP data to measure space utilization<\/h2>\n
\"From
Improving our space management using Microsoft Azure and AI is the focus for Nritya Reddy, Daniel Lee, Veeren Kumar Chimbili, Lakshmi Kothamasu, Sudhakar Sadasivuni, and Bharath Kumar.<\/figcaption><\/figure>\n

Our solution, Space Busyness Insights, uses our standard Wi-Fi WAP devices located throughout each building to calculate data on space utilization. This data includes identifying unused areas, occupied spaces and the crowd density, and the availability and use of common areas. By analyzing this data, we can make informed decisions about how to best allocate additional space or repurpose existing areas for more effective use. Additionally, we can plan for future real estate requirements.<\/p>\n

\u201c<\/span>We identified an opportunity to reuse the existing devices and the data that we already had from these devices,\u201d says Nritya Reddy, a senior product manager on the Microsoft Digital team. \u201cIt was a cost-optimized way of handling our requirements.\u201d<\/span><\/p>\n

Our employees\u2019 benefit from this solution is being able to view, in real time, the availability and activity in shared spaces such as kitchenettes and conference rooms. To implement this solution, we collaborated with our Infrastructure and security team, Innerspace (a third-party vendor), and Microsoft facilities managers. We integrated AI to enhance our data measurement and analysis capabilities, enabling us to create actionable plans for space management.<\/p>\n

\u201c<\/span><\/i>The era of modern smart experiences with IoT hardware demands innovative solutions that can be stitched across multiple devices and protocols with a cost-efficient design and architecture. I consider this as an opportunity to use the signals from two ecosystems to build secure, privacy-protected, smart building experiences. This gives us further opportunities to explore various use cases with WAP technology without additional hardware integrations,\u201d says Sudhakar <\/span>Sadasivuni<\/span>, principal group engineering manager, Microsoft Digital.<\/span>\u00a0<\/span>\u00a0<\/span><\/p>\n

Our innovative approach of repurposing existing devices for new requirements emphasized cost optimization and helped us be frugal with our resources.<\/p>\n

\u201cWe have an existing Wi-Fi infrastructure in all our buildings, provisioned via WAP devices by different vendors. They can provide a list of devices that are Wi-Fi- connectable and in the discoverable range of the given WAP device,\u201d says Reddy. \u201cBy employing artificial intelligence and machine learning<\/span><\/span><\/span> on this raw data, we can triangulate people density. Meaning, you would know how many people are in that specific area based on some of the devices that these people are carrying, either a laptop or a mobile phone, which are discovered by these WAP data points.\u201d<\/p>\n

We sell primarily to the largest enterprises, so we needed to build on a robust, highly secure, highly scalable, and universally trusted cloud infrastructure.<\/p>\n

\u2014 Matt MacGillivray, co-founder and VP of Research and Development at InnerSpace<\/p>\n<\/blockquote>\n

We partnered with InnerSpace, a vendor who has the logic and AI ML capabilities in their system to understand and make sense of the raw data that came from the WAP points and then provide meaningful people-count data.<\/p>\n

“We sell primarily to the largest enterprises, so we needed to build on a robust, highly secure, highly scalable, and universally trusted cloud infrastructure,\u201d says Matt MacGillivray, co-founder and VP of Research and Development at InnerSpace.<\/p>\n

He shared how they used Microsoft Azure services to run their logic and provide the output.<\/p>\n

\u201cWe used Azure Kubernetes to provide elastic capacity for our ingest pipeline and datastore, Azure App Services to run our client-facing web-based tooling, and Azure Container Instances to deploy containerized subsystems without needing to manage the machines running them,” MacGillivray says.<\/p>\n

InnerSpace also uses proprietary AI logic to ensure that people aren\u2019t counted double because they might be carrying more than one device. Based on the proximity of those devices and other logic and rules in place, they can help us determine space usage.<\/p>\n

The device identifiers are shared between systems in a hashed way. This ensures that specific devices discovered cannot be identified and personal identification information (PII) is protected. We performed stringent Microsoft architectural and data privacy reviews to ensure that no private data is being leaked at any stage. In addition to privacy, scaling and security are other key aspects considered when exchanging data with external systems.<\/p>\n

\u2014 Lakshmi Kothamasu, principal software engineering manager, Microsoft Digital<\/p>\n<\/blockquote>\n

We implemented this solution in our Redmond East Campus buildings, and through this process, we get the information we need for space utilization with these two goals in mind for our employees:<\/p>\n