Agriculture 4.0 involves the active implementation of precision farming, Internet of Things, wireless systems for collecting, archiving and processing data based on wireless sensor networks, as well as artificial intelligence to create predictive models for growing crops. To implement these technologies, high-level information systems are used. The goal of the proposed article is a comparative analysis of the functionality of digital platforms used in the Russian market, as well as ways to improve them. The article considers the capabilities and experience of using the following information systems on the basis of agricultural producers: AgroSignal, Cropio and Agrotechnologiya 2.0. Comparative analysis showed that these systems have similar functionality in terms of data collection, archiving and visualization through mobile and web applications. However, we note the lack of functionality for integrating the above information systems with the Internet of Things technologies offered on the market, in particular wireless sensor networks. Integration of our proposed solutions for managing wireless sensor networks into existing information systems will expand their functionality and improve the quality of data collection from agricultural facilities. Agriculture 4.0 represents a paradigm in farming practices through the active implementation of precision agriculture, the Internet of Things (IoT), and advanced wireless systems for data collection, archiving, and processing, as well as artificial intelligence for predictive modeling in crop cultivation. The aim of the proposed article is to conduct a comparative analysis of the functionalities of digital platforms currently utilized in the Russian agricultural market and to identify avenues for their enhancement. This article examines the capabilities and user experiences associated with three specific information systems employed by agricultural producers: AgroSignal, Cropio and Agrotechnologiya 2.0. The comparative analysis showed that these systems share similar functionalities regarding data collection, archiving, and visualization through mobile and web applications. However, there is a lack of integration with IoT technologies, particularly with respect to wireless sensor networks. We propose that integrating solutions for managing wireless sensor networks into these existing information systems for significant expansion of their functionalities. Such integration has the potential to enhance the quality of data collection from agricultural facilities, ultimately improving decision-making and operational efficiency within the sector.