five

AgriDataValue - Automatic Greenhouse Window Opening

收藏
Zenodo2026-03-11 更新2026-05-26 收录
下载链接:
https://zenodo.org/doi/10.5281/zenodo.18958751
下载链接
链接失效反馈
官方服务:
资源简介:
AgriDataValue aims to establish itself as the “Game Changer” in Smart Farming digital transformation and agri-environmental monitoring, and strengthen the smart-farming capacities, competitiveness and fair income by introducing an innovative, open source, intelligent and multi-technology, fully distributed Agri-Environment Data Space (ADS). To achieve technological maturity, fast and massive acceptance, AgriDataValue adopts and adapts a multidimensional approach that combines state of the art big data and data-spaces’ technologies (BDVA/ IDSA/ GAIA-X) with agricultural knowledge, monetization, new business models and agri-environment policies, leverages on existing platforms, edge computing and network/ services, and introduces novel concepts, methods, tools, pilot facilities and engagement campaigns to go beyond today’s state of the art, perform breakthrough research and create sustainable innovation in upscaling (real-time) agricultural sensor data, already evident within the project lifetime. --------------------------------------------------------------------------------------------------------------------------------------------- This dataset contains tabular data for the purpose of a greenhouse window opening percentage prediction. The file "Greenhouse_Climate_Window_data.xlsx" contains three environmental features outside the greenhouse which are: outside temperature outside relative humidity solar radiation intensity and also the opening percentage of each of the greenhouse windows. These two features ("Side 1 window opening", "Side 2 window opening") can be used as target values for a tabular data regression or a time-series regression task.   The file "Greenhouse_IoT_environmental_data.csv" contains IoT sensor measurements of several environmental features inside the greenhouse such as: air humidity air temperature soil temperature water content solar radiation level
提供机构:
Zenodo
创建时间:
2026-03-11
二维码
社区交流群
二维码
科研交流群
商业服务