How Data Analysis Is Shaping The Proptech Landscape
Having Completed his MS - Bioengineering from Texas A& M University, Aamer boasts of having 22 years of corporate industry experience, working with companies such as IMB, SAIC, Wipro Technologies, and Cisco Systems. Evolution of PropTech can be summarized as below:
PropTech1.0: Developers making decisions after receiving and analyzing a data set
PropTech2.0: Developers making decisions in realtime after generating insights from data
PropTech3.0: Decisions automatically recommended for developers in real time after continuous data analysis
Today, the industry is witnessing usage of AI/ML and AR/VR applications across all phases of the real estate life cycle from design to construction to tenant occupation. There is an emphasis on the following broad categories that will be addressed:
Productivity, Tenant Experience, Wellness, the other SaaS(Space as a Service)
Productivity
•Drones
•Significant decrease in time for: surveying, area/land insights (earth and soil constituents, water table and others)
•Construction progress/error margin: AI/image processing to analyze actual build vs planned build and raise alerts in advance and make correction beforehand. Track progress
•AR/VR
•Design Save time by showcasing planned design visually to all key stakeholders reduces the need to go back and forth for any changes or updates.
•Instantly transform and visualize 2D drawings into 3D.
•3D Digitization of buildings Ability of developers to easily map, track locate, monitor building assets.
Tenant experience
•Connected buildings
•Ability of tenants to interact with their physical spaces
•Provide a host of facilities/services for tenants through a centralized platform
•Ability of tenants to customize surroundings based on personal preferences (ex - seating, HVAC control,
lighting etc.)
•Community
•Provide networking opportunities for tenants
Wellness Data-driven actions
•CO2/air quality; Recycling: Monitoring and automatic trigger
The other SaaS - Space as a Service
•Data for all key stakeholders (developers as well as prospective tenants) for flexible workspaces with greater transparency
•Ability of developers to easily offer customizable spaces for various events/short terms rentals.
•Drones
•Significant decrease in time for: surveying, area/land insights (earth and soil constituents, water table and others)
•Construction progress/error margin: AI/image processing to analyze actual build vs planned build and raise alerts in advance and make correction beforehand. Track progress
•AR/VR
•Design Save time by showcasing planned design visually to all key stakeholders reduces the need to go back and forth for any changes or updates.
•Instantly transform and visualize 2D drawings into 3D.
•3D Digitization of buildings Ability of developers to easily map, track locate, monitor building assets.
Today, the industry is witnessing usage of AI/ML, and AR/VR applications across all phases of the real estate lifecycle
Tenant experience
•Connected buildings
•Ability of tenants to interact with their physical spaces
•Provide a host of facilities/services for tenants through a centralized platform
•Ability of tenants to customize surroundings based on personal preferences (ex - seating, HVAC control,
lighting etc.)
•Community
•Provide networking opportunities for tenants
Wellness Data-driven actions
•CO2/air quality; Recycling: Monitoring and automatic trigger
The other SaaS - Space as a Service
•Data for all key stakeholders (developers as well as prospective tenants) for flexible workspaces with greater transparency
•Ability of developers to easily offer customizable spaces for various events/short terms rentals.
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