Proptech – the integration of technology in the real estate industry – has seen a significant transformation in the last couple of years. In an effort to streamline processes, increase safety, drive efficiencies, and perfect the customer experience, proptech is reshaping the real estate market at an unprecedented rate.
Because of this massive rise in the use of technology, Edge AI learning is playing a crucial role in the evolution of the proptech industry for commercial real estate.
Scenera’s AI topology manager, Maistro, maximizes AI insights, providing a solution to the growing problem of how to best allocate artificial intelligence (AI) analytics in edge computing. Maistro helps organizations make the most of their AI investments by orchestrating Al across all of these different platforms and ensuring that it is being run in the most optimal location.
So how is Edge AI learning evolving the state of proptech in the commercial real estate industry?
1) Real-time Data Processing:
Edge AI learning allows for the processing and analysis of data at the edge of the network, closer to where the data is generated. In commercial real estate, this means that sensors and devices installed in buildings can collect and analyze data in real-time. This enables immediate insights into various aspects such as energy consumption, occupancy patterns, temperature, air quality, and security. Real-time data processing facilitates quick decision-making and optimization of building operations.
2) Predictive Analytics:
By deploying AI algorithms on edge devices, proptech solutions can leverage predictive analytics to anticipate future trends and outcomes. For example, Edge AI algorithms can analyze historical data to forecast maintenance requirements for building systems or predict occupancy patterns. This allows for proactive measures to be taken, such as scheduling maintenance tasks or optimizing space utilization, leading to cost savings and improved operational efficiency.
3) Reduced Latency and Bandwidth Requirements:
Edge AI learning reduces the reliance on cloud-based systems for processing and analysis. Instead, the AI algorithms are deployed directly on local devices or servers within the building. This reduces the latency associated with transmitting data to the cloud for processing and receiving results back. It also lowers the bandwidth requirements, as only summarized or relevant data needs to be transmitted to the cloud. This enables faster response times and reduces the burden on the network infrastructure.
4) Offline Functionality:
Edge AI learning allows for offline functionality, meaning that the AI algorithms can continue to operate even when there is limited or no internet connectivity. This is particularly beneficial for remote or disconnected areas where internet access may be unreliable. It ensures that critical functions, such as security monitoring or energy optimization, can still be performed locally without interruptions.
5) Enhanced Privacy and Security:
Edge AI learning addresses privacy and security concerns by processing data locally without the need for it to be transmitted to external servers. This helps to protect sensitive information and ensures compliance with data protection regulations. Additionally, the decentralized nature of edge learning reduces the attack surface for potential cyber threats, as the data remains within the local network.
6) Cost Efficiency:
Edge AI learning can lead to cost savings in the proptech industry. By performing data processing and analysis locally, there is a reduction in the amount of data that needs to be transmitted and stored in the cloud, which can result in lower infrastructure and storage costs. Moreover, the ability to optimize energy consumption, maintenance schedules, and resource allocation through AI-powered edge devices can lead to significant operational cost reductions.
Utilize Proptech in Commercial Real Estate
In summary, Edge AI learning is transforming the proptech industry for commercial real estate by enabling real-time data processing, predictive analytics, reduced latency and bandwidth requirements, offline functionality, enhanced privacy and security, and cost efficiency. These advancements contribute to improved decision-making, operational efficiency, and overall performance in the commercial real estate sector.
