International audienceIn order to meet the needs of modern agriculture, with the internet of things and related technologies, the author has developed a set of agricultural condition monitoring and diagnosing of integrated platform for experiment. The platform used the client and server mode, include environmental factor of monitoring platform, intelligent decision sub platform and expert remote science and technology advisory services subsidiary platform. Environmental factors collected by data acquisition module, and transmit through network. Audio and video data used the XMPP protocol extension Jingle transmission; Use the knowledge base, fuzzy theory, self learning algorithm of intelligent to achieve decision-making and control. The platform has been experimented in the vegetable greenhouses, which can carry out remote supervisory and automated control and expert remote diagnosis and consultation, improving the facilities agriculture management level

Air-conditionings have energy storage functions. Through reasonable aggregation control, the output tracking can be implemented for wind power with stronger fluctuation to enhance its utilization rate. Cloud technology and intelligent appliances enable the appliance vendor to implement information interaction with the air-conditioning through cloud platforms to realize flexible regulation. In this paper, a management and control method of air-conditioning based on cloud platform is established. Based on this structure, the air-conditionings are divided into several aggregation groups according to the similarity of parameters, and each group completes the consumption task collaboratively. The consumption evaluation model of the air-conditioning group is established. On this basis, the allocation problem on consumption task for the aggregated group is constructed to implement the optimal solution under the condition of guaranteeing the degree of completion and user comfort. Each group implements the control for air-conditioning inside the group through the sliding mode control model. The simulation experiment verifies that the algorithm can effectively follow the output of clean energy, while intervening less in the air-conditioning operation.

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