Traditionally, the process of looking for, buying, renting, or selling properties has been a manual task. People used to spend a lot of time shortlisting and finalizing their dream property. But in the era of digitization, the entire process has become highly streamlined, automated, and accurate. The real estate business is much more than just a ‘perfect house’ in an exotic location. It deals with huge volumes of data in terms of buyer/seller preferences, financial and risk-taking capabilities, etc.

The real estate sector is changing to accommodate a data-driven approach to solutions. AI and machine learning technologies assist real estate professionals streamline their efforts through automation and predictability. This is beneficial to both property purchasers and tenants.

Benefits of computer vision for Real estate

Below you can read about the most popular benefits:

1. Users can search the properties with a voice-enabled command

2. Prospects can search property listings that meet their requirements via mobile devices;

3. Technology increases the number of pictures real estate platforms can support.

4. Using Predictive property analytics to offer better recommendations

Applications of Computer Vision in Real Estate

Image Tagging

Image tagging takes advantage of the current technologies used in the real estate sector. There are millions of images available on the real estate portal. The metadata of these images can be used to provide a better experience to the user. The image search engine results can be improved drastically by using metadata. With advanced computer vision technologies, firms can avoid writing long descriptions about products on their websites.

The metadata can be used to tag specific items in the image so users can find further information about the properties they are interested in. With the addition of thousands of images to the platform every day, the technology can be vastly improved upon to provide a minimalistic, non-obtrusive user experience. Buyers can quickly identify properties and decorative materials that match their needs and preferences, and sellers can also provide better information to their clients.

Value Prediction

Determining the property value in real estate has always been a challenging task. Present appraisal techniques are mainly based on earlier selling price but fail to take into consideration other factors that contribute towards property value such as environmental changes, infrastructure improvements, transportation costs, etc. Machine learning-based tools help in resolving this issue by calculating property value keeping in mind all the above-mentioned factors. This gives accurate price estimates to brokers who can then make a steady initial offer to prospective buyers adhering to market standards.

Property Comparison

With the use of computer vision, users can compare properties room for room. Users can select properties by comparing various options and analyzing their space, amenities, natural lighting, and other features. With the thousands of images available online, computer vision can help users compare properties inch by inch. Multiple images available for a single room helps the user for a better comparison and provide a better judgment regarding the property.

With further development and research, the use of computer vision in real estate can transform the property buying and selling experience along with financial benefits for all parties involved. Combined with AR and VR, it has the potential to disrupt the real estate sector completely. Computer vision will provide users with a more photo-centric property-buying experience.

Enhanced data management

Estate brokers have to deal with huge chunks of data, including property appraisal reports, legal papers, sales details, zoning regulations, etc. As the broker is on the verge of finalizing a contract, the documentation increases and so does the data. Now, lease, partnership, and non-disclosure agreements are also added to the existing list of mandatory documents. Though in today’s scenario, everything is digital, still a human presence is required to deal with massive data.

Machine learning ensures that the data collected is accurate and authentic through continuous analysis. If any inconsistency is observed, such as invalid characters, missing signatures, vacant fields, etc, the machine learning-powered tool notifies it. This helps to securely store data without any replication and streamlines data management in the real estate business.

The Future

Advancements in machine learning have been made at a rapid pace, and the opportunities for real estate will continue to grow over the coming years and will likely be further accelerated by the Covid pandemic.

Since AI systems are proficient in synthesizing data and carrying out tasks, they can provide both buyers and sellers with quick and easy transactions. Best of all, these innovations can reduce operational costs and improve the quality of customer services. The age of enjoyable and frictionless real estate transactions is dawning.