| heal.abstract |
This paper is an overview of a large knowledge based operations optimization system that is partially in operation and in part under development for implementing deep knowledge schemes as well as adapting protocols and hardware to comply with the expected wave on IOT. With the development of sensing, wireless communication, and Internet technologies, we are now living in a world that is filled with various smart things - the Internet of Things. This paper introduces and prospects an emerging research area - the Embedded Intelligence (EI) for agricultural operations. This field, in its humanistic scope, aims at revealing the individual behaviors, spatial contexts, as well as social patterns and urban dynamics by mining the digital traces left by people while interacting with Internet of Smart Things (cameras, smart cars, smart cards, etc). In the agricultural sector we add mining of existing technology (books, articles, blue prints) to generate high depth Ontologies for reasoning and making pro-active decisions. We further include Intelligent Data Analysis to discover new knowledge from data records. The paper discusses the research history, characteristics, general architecture, major applications, and research issues of EI and exemplifies an application of the team in IOT Smart Irrigation. In this paper, a greenhouse management system based on knowledge supporting technology is designed. It includes three parts: a wireless sensor network (WSN), a service platform operating in Internet, and a decision-making support system (DMSS) based on knowledge supporting technology. The wireless sensor network is used to monitor and acquire all types of environmental information for the crop growth, such as air temperature, air relative humidity, CO2 concentration, substrate temperature, soil water content, etc. All data collected by WSN is sent to the service platform via Internet, and then the data are analyzed through DMSS based on cloud service technology. In the DMSS, the data from WSN are sent to the service platform where processed with expert's knowledge, and then derive an optimal decision to send back to ground equipment to control the greenhouse. This process would realize high resolution optimization management in greenhouse. The efficiency of the whole system based on IoT is expected to succeed in many aspects from environmental indices (IPM) to economic sustainability, based on targets set to the service by the grower. |
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