Enhancing building intelligence: Strategies for data insights and communication
The importance of a common language and semantics
The scenarios involving multiple city stakeholders necessitate interoperability and openness. From a technical point of view, all the participants have to speak the same language and have the same set of communication skills and data formats, and at the same time, they should not need to understand all the details of each participant to achieve a certain use case.
A building should not have to navigate through the intricacies of different systems and all the technical details of a car, a street light, or another building to acquire the data it requires. Instead, it should be able to pose general queries, such as “who can provide me with air quality data for a certain location?” or announce its “needs” for more hot water and receive a response.
For this to work, it needs a common language of things and their relationships (semantics), as well as a way to understand other participants’ needs and services.
The need for an abstraction layer in smart buildings
This is why there is a clear need for an abstraction layer to be set on top of the plethora of technologies for each of these stakeholders. For buildings, using semantic modeling and having a building operating system (BOS) built on open standards can help achieve just that.
Current Semantic modeling initiatives include:
- Real Estate Core
- Project Haystack
- Brick Schema
Use case: Reducing energy consumption, air pollution, and traffic congestion
To make the abstraction layer point clearer, let us focus on one potential use case. We can say it is in the interest of a city to reduce energy consumption, air pollution, and traffic congestion caused by cars. It has been identified that one reason for cars staying mobile in the streets and contributing to these issues is the lack of parking spots, which causes drivers to drive for longer times and at lower speeds while searching for a parking spot.
At the same time, other buildings might have extra capacity in their parking spots during different times of the day. For example, an office building’s garage might have a considerable capacity left empty during peak hours since many employees work from home.
After working hours, the whole garage might be empty and can be used to park cars or bikes for people living nearby. This can also apply to a retail store with empty garages at night or a house’s parking spot during the work day. Some of these garages might even have EV chargers that are setting idle most of the time. Imagine having your car tell you where to go for a free parking spot.
The free parking spot dilemma: What is the solution?
An ambitious company, let us call it Company X, wants to become the Airbnb of parking spots and let anyone offer these parking spots online. How do you identify the availability and number of free parking spots, and how do you communicate that to the outside world?
The answer for a homeowner with one parking spot might be easy, as this can be done manually on the “app” that Company X developed, set the GPS location of your garage once and manually set the parking space as “available” in the app when the spot is not being used.
For the business owners of a retail store or office building, where a high percentage of parking spots may be vacant, a more automated approach would be necessary. The office building might have an underground garage, and the property owner or operator could opt to install individual sensors for each parking spot. In contrast, the retail store might have an outdoor parking area equipped with a single camera system that is sophisticated enough to detect the number and location of empty parking spaces from streaming video footage.
The importance of scalability in smart building connectivity
For Company X to achieve scalability, its technology, such as an “app” for parking management, should be adaptable and easily integrated into various buildings with minimal effort, regardless of the specific parking technology used. If the company had to manually investigate the availability of parking technology in each building and then connect the necessary data from each piece of equipment to use in its app, the connection to each building would become a unique project, making it difficult for the company and its app to scale, become mainstream, and gain widespread adoption due to time and cost constraints.
In the real estate industry, this is currently the case. Company X would have to connect to each building individually and adapt to the technology available, limiting its scalability and success.
To achieve scalability, company x will need a standardized independent abstraction layer between its app and the building to enable its solution to interact seamlessly with different parking technology available in various buildings.
The potential of smart building technologies in making our cities more liveable
If Company X’s parking app was not limited by the need for adaptability and integration into each individual building the company could then focus its efforts on other areas of innovation. This could include the cost of parking in different times and locations, balancing the number of parking spaces available to the public versus those reserved for building occupants and visitors, adding additional services such as an electric vehicle (EV) and e-bike charging, enhancing the overall user experience, implementing online payments, and other features.
This, in turn, would attract more building owners, increasing adoption and benefiting all parties involved.