Real Time Automation on Real Estate using API

2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) Pub Date : 2022-02-16 DOI:10.1109/ICEEICT53079.2022.9768428

M. S. Bennet Praba, Udith Rajeev, A. Rathore, Ankit Kolangarath

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Abstract

Real estate can be confusing, unclear, disoriented and many a times the price or listings are put up randomly what the seller decides. Such a system makes it difficult for buyers to make reliable decisions also for a seller to determine what price must he put up the listing or what their property is worth. There are various aspects that decide the price of a property - proximity to public transport, cities, neighborhood and cultural aspects, availability, furnish status, etc. A model has to be deployed to provide accurate real estate decisions that are based on a variety of features and tags related to the property. To estimate such a value real time, we need a real time data source to help a community or individual determine the actual deserving value for their property they wish to buy or sell. This system looks to deploy well designed models that can adjust to variations in data due to geographical, economic and political differences by modelling real time data using an API

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使用API的房地产实时自动化

房地产可能会让人困惑、不清楚、迷失方向，很多时候，价格或房源都是卖家随意决定的。这样的制度使得买家很难做出可靠的决定，也使得卖家很难确定他必须在清单上列出的价格或他们的房产的价值。决定一处房产价格的因素有很多——距离公共交通的远近、城市、社区和文化因素、可用性、装修状况等。必须部署一个模型，以基于与该属性相关的各种特征和标记提供准确的房地产决策。为了实时估计这样的价值，我们需要一个实时数据源来帮助社区或个人确定他们希望购买或出售的财产的实际价值。该系统旨在部署设计良好的模型，通过使用API对实时数据进行建模，从而适应地理、经济和政治差异造成的数据变化

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2022 First International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT)

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