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Copyright ?2012American Scienti?c Publishers All rights reserved Printed in the United States of America SENSOR LETTERS V ol.10,514–522,2012An Intelligent Controlling System for Greenhouse Environment Based on the Architecture of the Internet of Things Hao Luo,Peiling Yang ?,Yunkai Li,and Feipeng Xu College of Hydraulic and Civil Engineering,China Agricultural University,Beijing 100083,China (Received:30June 2011.Accepted:20September 2011)Greenhouse farming possesses substantial potential in high-ef?ciency use of water,land and energy in food production.It is a critical issue to develop the methodology for better environment control of greenhouses.This paper proposes an intelligent controlling system for greenhouses based on the architecture of the Internet of Things.The wireless sensor nodes and relay nodes are designed associating the physical world with the information https://www.doczj.com/doc/066570300.html,ing 3G or TCP/IP network as the channel of the network of the Internet of Things,users can completely control the systems,treat and analyze data via browsers in any place and at any time without need for installing any special device or software.The system carries out the paradigm of the Dynamic Data Driven Application

System enabling the simulation to receive the continuous data injected from the perception layer of

the system and to dynamically make response.The faster-than-real-time simulation is implemented

based on the established self-adaptation model.The factors about the environments of crop growing

are predicted and evaluated.At the same time,the results produced by the simulation are fed back

to the system software to control the actions of executive devices in the real-time mode forming a

closed controlling loop.The management function of the system software allows to ?exibly set the

executive devises of the greenhouses and to establish the completely new controlling rules with

high degree of freedom.Consequently,the software system combined with the expert system can

adapt to various greenhouses in different types and sizes.

Keywords:Internet of Things,Dynamic Data Driven Application Systems,Wireless Sensor

Network,Intelligent Greenhouse,Zigbee.

1.INTRODUCTION The land area of greenhouses in China was as large as 3.35million hectares by 2008producing 51%of the total vegetables.1Continuously improving the quantity and quality of the products from greenhouses in China,which is subjected to scarcity of water and land resources,is crit-ically important to feed her large population.Greenhouse farming possesses substantial potential in high-ef?ciency use of water,land and energy in food production.Among others,controlling the environment of greenhouses is a major aspect.The critical issue is to develop the methodol-ogy with which greenhouse environment can be controlled following crop’s requirements.?Corresponding author;E-mails:yangpeiling@https://www.doczj.com/doc/066570300.html,;iqeqda@https://www.doczj.com/doc/066570300.html, A greenhouse is a system where multi-factor,strong nonlinearity,and complex coupling relationship coexist.

The comprehensive and convenient measurement of para-meters,therefore,is fundamental to effectively control greenhouse environment.For instance,an increase in the amount of sensors is usually needed in the hope of increas-ing the uniformity of the greenhouse environment.The deployment of the monitoring system in a greenhouse requires solving such problems as easy expansion,conve-nient installation and relocation,and low maintenance cost,etc.On the other hand,assembly of the information from scatter sensors causes evident signal decay and interfer-ence which may decrease the accuracy of the information,

further increasing dif?culties to control the environment

of greenhouses.Moreover,the constant increase in amount

and size of greenhouses sets an even higher demand on the managements of the greenhouse environments.514Sensor Lett.2012,Vol.10,No.1/21546-198X/2012/10/514/009doi:10.1166/sl.2012.1850

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For example,respectively managing every greenhouse dis-tributed in a large area implies more expensive manpower and higher cost if the present practice continues.The tra-ditional controlling on greenhouse environment still could not meet the requirements put by greenhouse development. The internet of things(IoT)has been a new paradigm in modern wireless communication area over the last few years.Its basic idea is the presence distributed around us of things which,through unique addressing scheme,are able to interact with each other and cooperate with their neighbors to reach common goals.2It is considered that the IoT could,like the present Internet,contribute invalu-ably to economic development.3The IoT has the advan-tage for environment monitoring.4–5A monitoring system based on the architecture of the IoT has features of?exi-ble deployment and relatively low cost in construction and maintenance.This type of systems timely offers reliable and detailed information about the changing environment and lets end-user make decisions and actuate the executive devices.The implement of this process needs the end-user simply to connect to web at any place.So,it is valuable to integrate the idea of the IoT into the monitoring and con-trol of greenhouse environment for meeting the require-ments put by greenhouse development.

In the practice of agricultural production,the direct measurement of some factors of the environment where the crop grows is dif?cult.For example,the soil mois-ture in the rooting zone has to be simulated by using the measured value at the surface of the soil.But current sim-ulation fails to trace the real?uctuation of the soil mois-ture.A dynamic data driven application system(DDDAS) is a powerful and new simulation application paradigm.6 This paradigm alters the traditional modeling approaches that employ models driven by static input data7in isola-tion and is unable to provide realistic,real-time forecasts resulting in distortion.Under the DDDAS paradigm,the real-time data acquisition injects real world data into the sophisticated simulation computation to more accurately analyze and predict dynamic change in local.8–9A DDDAS combines a simulation system with the real system to pro-duce a closed controlling system.This paradigm enable user to make proper decision and guide further data mea-surements.The continuous,dynamic data collection pro-vided by the perception layer of the IoT and the terminal browsers existing anywhere are just what a DDDAS needs. There are various types of greenhouses in practice.They are different not only in size also in the rules to actuate controlling.The greenhouses used for agricultural produc-tion may employ matured and conventional rules.There are still some greenhouses used for research and exper-imentation.In this case,their controlling rules are com-plicated and change often.They involve more executive devices and controlling factors such as variable periods of time,additional environmental parameters and other devices.The controlling software used for greenhouses has to have?exible setting scheme not only providing conven-tional controlling rules set in advance but also ability to conveniently set new rules.Also,the expert system,as a branch of the arti?cial intelligence,10can combines with the controlling rules to meet the requirements of different types of greenhouses.

This paper proposes a general-purpose,intelligent con-trolling system for greenhouses based on the architecture of the IoT.It follows the idea of the IoT with respect to monitoring and the information transmission,namely pro-viding an application oriented IoT which smoothly con-nected the perception layer of the IoT with the internet, and acted as the channel of the network layer of the IoT. This system realized centralized management and scat-ter control by using the terminal connected with inter-net at any https://www.doczj.com/doc/066570300.html,ing this system,users augment their capability of remote interaction with the external,real world realizing the combination of the perception,the channel,and the application.By using the paradigm of a DDDAS,this system dynamically responses to the data continuously injected,makes the simulation and prediction more accurate.These simulation and prediction are fed back to the system software thereby helping users make decision.The system employs the general-purpose setting scheme.The DDDAS combined with the expert system provides the ability to?exibly set control.

2.SYSTEM REALIZATION

As shown in Figure1,the system consists of sensor nodes,relay nodes,a system of environmental monitoring and control,the system software,the expert system and DDDAS and a remote terminal.Based on the architecture of IoT,the sensor nodes,the relay nodes and the sys-tem of environmental monitoring and control were devel-oped to realize the wireless senor network(WSN)and the function of wireless control making up a sub-internet of things possessing the functions such as sense,feed-back and interaction.This sub-internet of things designed in this way was able to control all sensors in the wire-less mode and to collect the environmental information like temperature,relative humidity,soil water content,sun-shine,carbon dioxide inside or outside the greenhouses on the one hand,and on the other hand,to manage,in the wireless mode,the controlling devices for irrigation,sky-light,ventilator,wet curtain,sunlight-proof curtains inside and outside the greenhouse,lamps and heating equipment. The information collected,via the system of environmen-tal monitoring and control,was transformed into the data that could be recognized by the system software.The sys-tem enabled the sub-internet of things to merge into wider network,using the B/S architecture via3G or wired mode as the cannel in the IoT.Thereby the interconnections of machine to machine and machine to man were actualized. The system software ran in the server that a set of com-puter served as.The system software,in combination with

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The envi-ronment inside &outside the greenhouse The sensor node The control devices in the greenhouse The relay node The system for environ -mental monitoring and control The system software The expert system &DDDAS The remote terminal 3G network TCP/IP network Wireless sensor network (WSN) Wireless control Fig.1.Sketch diagram of the system architecture.the DDDAS and the expert system based on the knowl-edge base which is continuously accumulated,provided growers located in different places with intelligent control-ling schemes recommended for different plant crops.The DDDAS conducted faster-than-real-time simulation of the monitored objects and actuated the controlling devices to regulate the environment in accordance with the simulated results.In the case of wireless communication,all sites where sensors were located might conveniently be changed and all devices used to control the environment of the green-house could wirelessly be turned on or off.Where the wireless communication was not appropriate,the sensor nodes and the relay nodes could be connected with the system of the environmental monitoring and control in a bus https://www.doczj.com/doc/066570300.html,rmation Collection and Device Control There are various

greenhouses with respect to types and amounts of sensors and controllers which are deployed in different way and at different sites as well.The hard-ware of the proposed system,therefore,employed mod-ular design to facilitate the applications of the system to the various greenhouses only by adding or reducing the Fig.2.The front-end module and the collecting module.

amount of the modules.Also,the cost and the power con-sumption would be lowered.A front-end module,a col-lecting module (Fig.2)and a controlling module were used to constitute the hardware for information collection and device control.The front-end modules acted as the sensor nodes and the relay nodes respectively.The collect-ing module and the controlling module de?ned the infor-mation from different sensors and from the status of the devices.Then,the information was summarized and sent to the system software situated in the server.At the same time,the controlling information was sent by the software back to the front-end module actualizing the collection of the environmental information and the control over the devices.There are a lot of papers about the sensor network in the literature in the last years,mainly discussing such problems as energy ef?ciency,reliability,robustness,etc.11According to the particular situation of the greenhouses,a sensor network was proposed.Although multiple sen-sors are involved in the measurements of the greenhouse environments,the signals produced by those sensors are only electric current,voltage and pulse in accordance with the signal classi?cation.The front-end modules supported the signals of 4–20mA,0–2voltage and pulse that cov-ered the most sensors used in greenhouse environments.

Consider the case where the soil moisture was measured as an example,soil moisture sensor AQUA-TEL-TDR was selected.The instrument that utilizes the principles of time domain re?ection using the difference of the dielectric between water and the other media in the soil can measure

the soil water content.The errors caused by a TDR instru-

ment installed in reasonable soil conditions are less than

3%,with short preheating time,1 A/ C of temperature

output and 4–20mA of output signal.

The signal was converted,via a resistance,to a value of voltage (Fig.3)which was transmitted to the Micro Controller Unit C8501F410where it was ?nally con-verted to digital signal.The C8501F410device (Fig.4)is fully integrated,low power,mixed-signal system-on-a-chip MCU,have true 12-bit 200ksps ADC with analog 516Sensor Letters 10,514–522,2012

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Fig.3.The schematic diagram for current signal collection.multiplexer and 24analog inputs.With on-chip Power-On Reset,VDD monitor,Watchdog Timer,and clock oscilla-tor,the C8051F410device is truly standalone system-on-an-chip solutions.The device is speci?ed for 2.0-to-2.75V operation over the industrial range (?45to +85 C).12Each of the front-end modules supported 4input links with which different types of sensors could be connected depending on actual demands.At the same time,each of Fig.4.The C8051F410processor circuit diagram.

the front-end modules with 2links of switch signal outputs

?nally actuated the motors and the magnetic valves actu-

alizing the actions of various devices,via auxiliary relays,

guard circuit and contactor.

The collecting modules and the controlling modules

de?ned the information transmitted from the front-end

modules in the way of identifying the physical meaning

and measuring range of the various parameters that were

being monitored.In order to operate ef?ciently,the de?ni-tions of the conventional signals of various sensors were stored in those modules in advance.It was convenient that the system software selected the prestored signal de?ni-

tions when operating.But there were some sensors whose linearity was poor.In the case of soil moisture sensor,

for example,only the signal pieces separated into small intervals could be regarded as linear.In order to pick out relatively exact measurements,the de?nitions of the small

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intervals of the signals were tabulated and stored in the modules.Accordingly,the relatively exact values could be obtained by comparing the output signals with the inter-vals.In reality,this practice was faster and more precise than curve-?tting.There were one or more than one col-lecting modules and controlling modules in a whole sys-tem.Each of the collecting modules could involve several front-end modules.All of the environmental information obtained by those collecting modules was transmitted to the system software via the bus RS485under relevant pro-tocol.Then,the system software sent commands to actuate the devices in the greenhouse to achieve corresponding actions.The controlling modules included fundamental control logic.When the communication between the controlling modules and the system software was interrupted for some reason,the standby control logic would automatically start to guarantee all executive devices of the greenhouses working safely and to raise the alarm.The controlling modules were connected to the local/remote rotary switch which determined whether the start-stop button situated at the executive devices was effective or not.When the switch was in the status of remote site,the start-stop button situated at the executive devices was not effec-tive.The command from the controlling modules was needed to trigger the executive devices in the greenhouse.When the switch was in the local status,the command from controlling modules was not effective.The manip-ulation of the executive devices in the greenhouse had to be achieved manually by the start-stop button.In this case,the controlling modules would only transmit the collected environmental information to the system soft-ware.The collecting modules and the controlling modules employed the Micro Controller Unit EMGA64as the cen-tral unit.The EMGA64,which is a much matured one with strong I/O function,provides 64K byte of In-System Pro-grammable Flash with Real-While-Write capabilities,2K bytes EEPRO,4K bytes SRAM,53general-purpose I/O lines,32general purpose working registers.132.2.Data Transmission System Based on the Internet of Things Based on the idea of the IoT,this system took an architec-ture which included three layers.WSN composed of the sensors,data acquisition proxy,communication proxy and ZigBee wireless transmission is the perception layer in the IoT architecture.The communication proxy,middle-tier and 3G or TDP/IP network constitute the network layer in the IoT architecture (Fig.5).The remote browsers,the management system of the greenhouse and the relay nodes constitute the application layer in the IoT architecture.This system,as a cyber-physical system (CPS),was able to monitor and control the behaviors of the physi-cal devices in the greenhouse.The sensors played a part

Fig.5.Sketch diagram of the data transmission based on the architecture of IoT.in perceiving environmental factors.The relays played a part in controlling the devices in greenhouses.As active power nodes,the collecting modules and controlling mod-ules were equipped with IoT oriented data link layer pro-tocol,satisfying the needs for information collection and

transmission of control command with features of high ef?ciency and energy-saving,and satisfying the needs for interaction application in the perception layer of the IoT.The controlling modules coordinated with the software played a part in the dual-mode gateway connecting the WSN with the internet.They smoothly connected the per-ception layer of the IoT with the internet,and acted as the channel of the network layer of the IoT.The servers,acting as the nodes of the internet and matching with the con-trolling software,provided standard access interfaces of the internet and the protocol for interaction,standard com-puting platform,service invocation and the management interface.

In order to realize the perception layer in the IoT based

on WSN,the front-end modules and the collecting mod-

ules of the system were equipped with ZigBee possessing

the feature of wireless transmission.The XBee-Pro was

used as radio frequency module.ZigBee is one of commu-

nication techniques with qualities of less cost and lower power consumption suitable for a small area.The MESH network topology based on ZigBee has big advantages of Ad Hoc network and realizes communication in the mode of multi-hop.This topology can constitute extremely complex network and has the features of self-organization and self-cure.14Accordingly,ZigBee,as a wireless trans-mission network,was very appropriate for applying to the environment of the greenhouse.It was convenient to expand the system and to solve the problem of signal cover in local.The XBee-Pro 802.15.4module operates within the ISM 2.4GHz frequency band.The XBee-Pro modules 518Sensor Letters 10,514–522,2012

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are embedded solution providing wireless end-point con-nectivity to devices.These modules use the IEEE 802.15.4networking protocol for fast point-to-multipoint or peer-to-peer networking.They are designed for high-throughput application requiring low latency and predicable commu-nication timing 15(Fig.6).Another effect taken by the front-end modules was to provide sensors with power supply.The working current of the soil moisture sensors was several of tens of mA.The power consumption of a module was more than 1W

as connected with 4sensors.If rechargeable battery had been used,allowing for the response time of the sensor,the frequencies of recharging electricity would have been high even though the sampling interval was so long as several of minutes.Besides,the greenhouse was a wet environ-ment that was rather harmful to the life-span of batteries.The results of using battery as power supply inevitably were expensive maintenance cost and the battery pollution.On the basis of analysis above,DC12V transformer was used to provide all modules with power supply.The collecting modules existing in ZigBee multi-hop network,as the coordinator,took the effects including set-ting parameters for network booting,assigning addresses to the added devices as well as maintaining the routing table.The functions of the front-end modules,as the router and the end devices,were to discover the network,to build up or to disconnect the network and to maintain the rout-ing table.The routes among the sensor nodes consisting of the front-end modules and collecting modules were auto-matically set up via ad hoc.The network with no center and self-organization was formed.It collected the environ-mental information and then transmitted it out.Wiring in the greenhouses was dif?cult for seasons of complexity of its environment,a large amount of the sensors.Also,the excessively long wire could cause evident signal decay and interference.Besides,the wired system was dif?cult to install and limiting to expand the system.The mainte-nance cost is high as well.But the perception layer based on WSN overcame these dif?culties to a large extent.16Although there have not been general standards for the IoT,distinctions between the IoT and the

traditional Fig.6.XBEE pro processor circuit diagram.internet are evident.The IoT associates the physical world with the information world.17The communication proxy produces this effect.As “the last kilometer”of the IoT,WSN transmitted the controlling information to the executive devices as the environmental information was collected and transmitted to the internet.Because the trans-mitting distance of WSN was limited and excessive layers lead to swift increase in transmission load,time delay and power consumption,WSN alone could hardly realize the ubiquitous network connection.After WSN generated sub-networks,only did WSN combine with internet with IP,especially via wireless mode,the ubiquitously mutual con-nections could really be realized.

Because WSN and the present internet were hetero-geneous of each other,inserting a middle layer had to be needed.This middle layer was a dual mode gateway enabling connection with the two networks.In the situa-tion of the greenhouses,only the remote controlling was not adequate,and the local management system was neces-sary.In this case,a direct connection between the control-ling nodes and wireless gateway was no longer signi?cant.In the proposed system,therefore,the middle layer was accomplished by the software coordinated with the con-trolling modules.The computer acting as WEB server con-nected with the internet via cable or 3G network providing standard access interface of the internet,the protocol for interaction,and the management interface.Accordingly,the control over the system was realized without temporal and spatial constraints.

The management system installed within the green-houses included communication service program,the data server and WEB server.The communication service pro-gram was responsible for information collection,feedback of the status of executive devices and sending the control-ling information following the protocol ?xed in advance.The data server included the information about the struc-ture of the greenhouses,the environmental information collected,the status of the devices in the greenhouses and the controlling modes.In order to realize the communi-cation of man to things via the ubiquitous network under

the architecture of the IoT,the WEB server used the B/S

architecture and generated dynamic pages so that the mon-

itoring and control of the environments of the greenhouses

were achieved in remote browsers via the internet.When

the browsers on the remote PC made requests for service

to the WEB server via the internet,the WEB server would

send the requested data to the business logic layer by

using HTTP protocol after the users passed the authentica-

tion.While receiving the requests from users,the business

logic layer performed the extended application program,

connected with the data server and applied to the data

server for data processing.By the requests,the data server

extracted the data from database or modi?ed the data in

the database and then submitted the result to the WEB

server.The WEB server sent the results back to the remote Sensor Letters 10,514–522,2012519

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PC,at the user’s requests.The browser on the remote PC received the page ?les and displayed them on the browser.In this process,the communication service program stored the received information about the environment and the status of the devices in the database,and transmitted the commands about controlling devices of the greenhouse to the controlling modules and then to the relay nodes,via ZigBee network,to actuate controlling devices and to actu-alize corresponding actions.The communication service program used in the proposed system was programmed by using C ++.The database server was based on SQL server.The WEB server was based on Jakarta Tomcat.The proposed system,based on the architecture of the IoT composed of the perception layer,the network layer and the application layer,is able to access and control the sub-systems via browsers in any place where there is network connection and at any time without need for installing any special device or software.The cluster man-agement of several of greenhouses distributed in a large area can be realized via the remote monitoring and con-trol with manpower https://www.doczj.com/doc/066570300.html,ing remote browsers,the system realizes to timely understand the working status of the sensors and devices within the greenhouses,to actual-ize the control over the sensors and the executive devices,to collect and store various historical data of the green-houses,to provide growers with the scienti?c grounds and technical support for the optimal greenhouse environment and crop growing and to provide the remote instructions for setting-up of the system parameters.2.3.System Software The system software employed B/S architecture.The mon-itoring and control was all achieved by the browser.The system software included system setting module,expert system and DDDAS module,real-time and control moni-

toring module and the statistics and report module.As a

general-purpose controlling system for greenhouse,this

software was applicable to greenhouses in different type

and size only by making some sensor,controlling devices

and control rules added to or removed from the system

setting module.It meant:First,the types of the sensors

and the controlling devices in the software were optional

making them consistent with those actually installed in the

greenhouse.Besides,the types of devices setting in the

software in advance,new types of the devices could be

added only by setting several of parameters in accordance

with the rules.Second,not only the amount of various

devices could be added or reduced but also the positions

of the devices and the deployments of the hardware could

be set up in the software by mouse clicking.Third,the

rules about device controlling and de?nitions of the sen-

sors could be modi?ed by either making selection from the

predetermined or setting new ones suitable for the actual

requirement.The new controlling rules of devices with high degree of freedom could be de?ned.The devices were allowed to properly operate even under simultaneous in?u-ence of several of factors such as time,multi-sensors as well as the status of other devices.The microclimate within a greenhouse is such a special environment that various effects,like multi-factor,strong nonlinearity,and complex coupling relationship,coexist there.All of the effects evidently in?uence each other.For instance,skylight,ventilator,sunlight-proof curtain and wet curtain all have the effect to lower the tempera-ture,but the humidity must be changed while the tempera-ture is dropping down.Similarly,the temperature must be in?uenced as the illumination changes.The feedback and coupling relationships between various executive devices and the environmental factors have to be carefully ana-lyzed so that the crop requirements for the greenhouse environment at different growing stages would be met.The proposed system software,allowing for both the produc-tion demand and service to the research,gave abundant setting for ?exible controlling modes and combined opera-tion of the devices based on time-segmented management.Furthermore,all setting could easily be modi?ed depend-ing on user’s demand whenever needed (Fig.7).The traditional automatic control is means that hardly can accomplish the task regulating the environment of the

greenhouse to fully adapt to the requirement of plants.Intelligent control has become a recent trend in develop-ment of the greenhouse.The proposed system software provided the modules of DDDAS and the expert system

and their interface.

DDDAS (Dynamic Data Driven Application Systems)

involve models that are driven at execution-time by

dynamic inputs,of archival or real-time data genera-tion/collection,in order to continually improve compu-tationally based analysis and prediction methods,and

in https://www.doczj.com/doc/066570300.html,puter screen capture of the software.

520Sensor Letters 10,514–522,2012

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reverse,to control and improve the measurement processes and data discovery and management.18It is a type of cybernetic idea proposed by U.S.National Science Foun-dation.It is used to simulate complex systems contribut-ing to making decision in real-time mode.The traditional simulations,which employ models driven only by static data inputted before starting,have to restart the simula-tion system as new data is inputted so that the simula-tion always lags behind the real system.Its application to the real-time mode is not adequate especially facing complex situation.The DDDAS module in the proposed system software developed capability to accept real-time data of the environmental parameters and implemented faster-than-real-time simulation,established dynamic inter-action,and intelligently made suggestion on environmental parameters.It took the effect to overcome the shortcoming produced by only relying on sensors for the environmental information.For example,the soil moisture sensors mea-sured soil moisture in the surface layer of soil and injected the constantly changing data into the DDDAS module. Using the dynamic data,the module conducted faster-than-real-time simulation to water content distributed in the soil pro?le of the rooting zone.A self-adaptation model was established to predict the required objective and to make modi?cations accordingly.And then,the software and the greenhouse controlling system operated the con-trolling devices of the greenhouse,in real-time mode,to regulate soil moisture and completed the loop between the real system and the simulation system realizing the symbiotic simulation system.

The expert system in the software adopted object-oriented design idea.It was established on the knowledge base which has continually been accumulated.It offered solutions to the speci?c controlling demand following related reasoning mechanism.For instance,this expert sys-tem was able to recommend irrigation program or control-ling regulation of the irrigation by using the database and the reasoning mechanism after collection of the informa-tion about the crop type,the location of the greenhouse, soil type,farming system and the irrigation device used. Besides,different emphases could be distinguished.For example,water saving or high yield,which one was pre-ferred by the grower.The program or regulation deter-mined in this way could automatically be performed once con?rmed by the user.

3.CONCLUSIONS

The growth and development of crop plants all respond to various environmental factors.Taking advantage of the characteristics of greenhouses and dynamically regulating the environmental factors associating with crop plants are the key to achieve production with high yield and quality under the conditions of given plant varieties and farming systems.For this purpose,this paper proposes an intel-ligent controlling system for greenhouses based on the architecture of the IoT.Its main characteristics are: (1)The proposed system is based on the architecture of the https://www.doczj.com/doc/066570300.html,ers can completely control the systems,treat and analyze data via browsers in any place where there is network connection and at any time without need for installing any special device or software.Consequently, centralized management and scatter control can be real-ized in a large area.The modularized wireless nodes can ?exibly deploy sensors or greenhouse controlling devices resulting in ubiquitous connection.A dual-mode gateway is inserted in the data transmission system so that the sys-tem can be connected with internet.Besides the system can manually be manipulated in local,that is particularly suitable for the greenhouse industry.The system which is based on the architecture of the IoT enables the green-houses to?exibly associate the physical world with the information world,strengthening its capability of percep-tion and interaction,actualizing the mutual connection of machine to machine and machine to man.

(2)The system tries to carry out the paradigm of DDDAS. The continuous and dynamic data of the soil moisture in the surface layer of the soil is injected into the DDDAS module.The DDDAS module responds to the data injected and establishes the dynamic self-adaptation model,then uses the simulated result to control the devices within the greenhouses and to regulate the soil moisture.A symbiotic and dynamic fed-back control system is formed between the simulation system and the real system.The main feature is that it is able to continuously respond to the changing monitored data,and to evaluate and predict its in?uence establishing the dynamic interaction and deter-mining the suitable values.

(3)The sub-system of the system setting in the software is of general-purpose.This property allows the sensors and the devices within the greenhouses to?exibly be set with respect to their types,amounts and deployment style.Con-sequently,the new controlling rules with high degree of freedom and different types of controlling can be estab-lished for widely used to different types of greenhouses and adapting to the complexity of greenhouse controlling.

(4)The system software combined with the expert sys-tem provides users with recommended solution which can automatically be performed once con?rmed by the users.Established on the rule-base and the knowledge-base,which has continually been accumulated,the expert system is able to make a judgment and to automatically determine the environment and the controlling scheme suitable for the crop growth at speci?c growing stages, meeting the requirements for different seasons,types of crops,and locations and irrigation devices. Acknowledgments:This work was supported by the Project of the Internet of Things and Intelligent Sys-tem for Irrigation(Innovation Fund for Technology Based

Sensor Letters10,514–522,2012521

Delivered by Ingenta to:Biblioteca de la Universitat de Barcelona IP : 140.114.78.139Sun, 10 Jun 2012 02:38:14R E S E A R C H A R T I C L E Firms),Project of Intelligent Decision Techniques for Pre-cise Irrigation and Fertilizing (Beichen Water Authority,Tianjin),Project of The Key Techniques for Energy Sav-ing of Greenhouses (Beijing Municipal Commission of Education),and CAU Xianfei Agricultural Engineering Technology Co.,Ltd.(Beijing).References and Notes 1.M.Zhu and C.Zhou,New Developments of Protected Agriculture in China,https://www.doczj.com/doc/066570300.html,/,accessed on August 2009(2009).2. D.Giusto,A.Iera,G.Morabito,and L.Atzori (eds.),The Internet of Things,Springer,New York,USA (2010).3.National Intelligence Council,Disruptive Civil Technologies—Six Technologies with Potential Impacts on US Interests Out to 2025-Conference Report,https://www.doczj.com/doc/066570300.html,/nic/confreports_dis-ruptive_tech.html,April (2008).4.S.Duquennoy,G.Grimaud,and J.-J.Vandewalle,The web of things:interconnecting devices with high usability and performance,International Conference on Embedded Software ,HangZhou,China (2009),pp.323-330.5.L.Atzori,A.Iera,and G.Morabito,Computer Networks ,54,2787(2010).6.NSF Workshop,Dynamic Data Driven Application Systems NSF Workshop Report ,https://www.doczj.com/doc/066570300.html,/cise/cns//dddas/,March (2000).7. D. D.Knight,Data driven design optimization methodol-ogy,a dynamic data driven application system,International Conference on Computational Science ,Melbourne,Australia (2003),pp.329–336.8. C. C.Douglas and Y .Efendiev,Computers Math.Appl.1633(2006).9.Y .Ouyang,S.M.Luo,H.L.Cui,Q.Wang,and J.E.Zhang,Eco-logical Engineering 616(2011).10.N.J.Nilsson,Arti?cial Intelligence A new synthesis,Morgan Kaufmann Publishers,Inc.,San Francisco,California,USA (1998).11.I.F.Akyildiz,W.Su,Y .Sankarasubramaniam,and E.Cayirci,Com-puter Networks 38,393(2002).12.C8051F410/1/2/3ISP Flash MCU Datasheet,https://www.doczj.com/doc/066570300.html,,accessed on July 2007.13.ATmaga648-bit Microcontroller with 64K Bytes In-System Programmable Flash Datasheet,https://www.doczj.com/doc/066570300.html,.14.I.Howitt and J. A.Gutierrez,Wireless Communications and Networking 1481(2003)15.XBee/XBee-PRO ZB (S2)Modules Product Manual,https://www.doczj.com/doc/066570300.html,.16.J.Zheng and A.Jamalipour,Wireless Sensor Networks,A Networking Perspective,John Wiley and Sons,Inc,U.S.A (2009).17.S.Haller,S.Karnouskos,and C.Schroth,The Internet of Things in an Enterprise Context,Future Internet–FIS,LNCS,Vienna,Austria (2008),V ol.5468,pp.14–28.18.NSF Workshop,Dynamic Data Driven Application Systems NSF Workshop Report ,https://www.doczj.com/doc/066570300.html,/cise/cns//dddas/,January (2006).

522Sensor Letters 10,514–522,2012

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数据库管理系统的介绍 Raghu Ramakrishnan1 数据库(database,有时拼作data base)又称为电子数据库,是专门组织起来的一组数据或信息,其目的是为了便于计算机快速查询及检索。数据库的结构是专门设计的,在各种数据处理操作命令的支持下,可以简化数据的存储,检索,修改和删除。数据库可以存储在磁盘,磁带,光盘或其他辅助存储设备上。 数据库由一个或一套文件组成,其中的信息可以分解为记录,每一记录又包含一个或多个字段(或称为域)。字段是数据存取的基本单位。数据库用于描述实体,其中的一个字段通常表示与实体的某一属性相关的信息。通过关键字以及各种分类(排序)命令,用户可以对多条记录的字段进行查询,重新整理,分组或选择,以实体对某一类数据的检索,也可以生成报表。 所有数据库(最简单的除外)中都有复杂的数据关系及其链接。处理与创建,访问以及维护数据库记录有关的复杂任务的系统软件包叫做数据库管理系统(DBMS)。DBMS软件包中的程序在数据库与其用户间建立接口。(这些用户可以是应用程序员,管理员及其他需要信息的人员和各种操作系统程序)。 DBMS可组织,处理和表示从数据库中选出的数据元。该功能使决策者能搜索,探查和查询数据库的内容,从而对在正规报告中没有的,不再出现的且无法预料的问题做出回答。这些问题最初可能是模糊的并且(或者)是定义不恰当的,但是人们可以浏览数据库直到获得所需的信息。简言之,DBMS将“管理”存储的数据项,并从公共数据库中汇集所需的数据项以回答非程序员的询问。 DBMS由3个主要部分组成:(1)存储子系统,用来存储和检索文件中的数据;(2)建模和操作子系统,提供组织数据以及添加,删除,维护,更新数据的方法;(3)用户和DBMS之间的接口。在提高数据库管理系统的价值和有效性方面正在展现以下一些重要发展趋势; 1.管理人员需要最新的信息以做出有效的决策。 2.客户需要越来越复杂的信息服务以及更多的有关其订单,发票和账号的当前信息。 3.用户发现他们可以使用传统的程序设计语言,在很短的一段时间内用数据1Database Management Systems( 3th Edition ),Wiley ,2004, 5-12

英文文献及翻译:供配电系统(1800字)

供配电系统 摘要:电力系统的基本功能是向用户输送电能。lOkV配电网是连接供电电源与工业、商业及生活用电的枢纽,其网络庞大及复杂。对于所有用户都期望以最低的价格买到具有高度可靠性的电能。然而,经济性与可靠性这两个因素是互相矛盾的。要提高供电网络的可靠性就必须增加网络建设投资成本。但是,如果提高可靠性使用户停电损失的降低小于用于提高可靠性所增加的投资,那么这种建设投资就没有价值了。通过计算电网的投资和用户停电的损失,最终可找到一个平衡点,使投资和损失的综合经济性最优。 关键词:供配电,供电可靠性,无功补偿,负荷分配 1 引言 电力体制的改革引发了新一轮大规模的电力建设热潮从而极大地推动了电力技术革命新技术新设备的开发与应用日新月异特别是信息技术与电力技术的结合在很大程度上提高了电能质量和电力供应的可靠性由于技术的发展又降低了电力建设的成本进而推动了电网设备的更新换代本文就是以此为契机以国内外配电自动化中一些前沿问题为内容以配电自动化建设为背景对当前电力系统的热点技术进行一些较深入的探讨和研究主要完成了如下工作. (1)提出了配电自动化建设的两个典型模式即―体化模式和分立化模式侧重分析了分立模式下的配电自动化系统体系结构给出了软硬件配置主站选择管理模式最佳通讯方式等是本文研究的前提和实现平台. (2)针对配电自动化中故障测量定位与隔离以及供电恢复这一关键问题分析了线路故障中电压电流等电量的变化导出了相间短路工况下故障定位的数学描述方程并给出了方程的解以及故障情况下几个重要参数s U& s I& e I& 选择表通过对故障的自动诊断与分析得出了优化的隔离和恢复供电方案自动实现故障快速隔离与网络重构减少了用户停电范围和时间有效提高配网供电可靠性文中还给出了故障分段判断以及网络快速重构的软件流程和使用方法. (3)状态估计是实现配电自动化中关键技术之一本文在阐述状态估计方法基础上给出了不良测量数据的识别和结构性错误的识别方法针对状态估计中数据对基于残差的坏数据检测和异常以及状态量中坏数据对状态估计的影响及存在的问题提出了状态估计中拓扑错误的一种实用化检测和辩识方法针对窃电漏计电费问题独创性提出一种通过电量突变和异常分析防止窃电的新方法并在潍坊城区配电得到验证. (4)针对配电网负荷预测建模困难参数离散度大以及相关因素多等问题本文在分析常规负荷预测模型及方法基础上引入了气象因素日期类型社会环境影响等参数给出了基于神经网络的电力负荷预测方法实例验证了方法的正确性.

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外文翻译中文

运作整合 供应链协作的首要问题是提高运作整合的程度。供应链协作课达到的好处,直接关系到捕捉效率之间的职能的企业,以及全国的企业,构成了国内或国际供应链。本章重点阐述的挑战,一体化管理,由研究为什么一体化创造价值,并通过详列的挑战,双方的企业集成和供应链整合。必不可少的供应链流程是确定的。注意的是,然后向信息技术提供,以方便集成化供应链规划。本章最后审查了定价。在最后的分析,定价的做法和政府是至关重要的供应链的连续性。 为什么整合创造价值 基本的优点与挑战的综合管理介绍了在第1章。进一步解释整合管理的重要性,有用的指出客户都至少有三个角度的价值。 传统的角度来看,价值是经济价值。第二个价值的角度来看,是市场价值。 实现双方经济和市场价值是很重要的客户。然而,越来越多的企业认识到商业上的成功也取决于第三个角度来看,价值,被称为关联性。 物流一体化目标 为实现物流一体化的供应链背景下,6个业务目标必须同时取得:( 1 )响应,( 2 )差额减少,( 3 )库存减少,( 4 )托运巩固,( 5 )质量,( 6 )生命周期支持。的相对重要性,每个直接关系到公司的物流战略。 响应 一公司的工作能力,以满足客户的要求,及时被称为反应。作为一再指出,信息技术是促进反应为基础的战略,允许业务的承诺被推迟到最后可能时间,其次是加速投放。实施对应策略服务,以减少库存承诺或部署在预期客户的需求。响应服务转向业务重点从预测未来的需求,以容纳顾客对快速订单到出货的基础上。理想的情况是,在一个负责任的系统中,库存是没有部署,直到客户承诺。支持这样的承诺,公司必须有物流的属性,库存的可用性和及时交付,一旦客户订单收到。 差异减少 所有经营领域的物流系统很容易受到差额。方差结果从未能履行任何预期的层面后勤业务不如预期。举例来说,毫不拖延地在客户订单处理,意想不到的干扰,以便选择,抵港货物损坏,在客户的位置,和/或未能提供在适当的位置上的时间,所有创造无计划的差异,在订单到交货周期。一个共同的解决办法,以保障对不利的差异是使用库存安全库存,以缓冲行动。这亦是共同使用的首选运输,以克服意想不到的差异延误交货计划。这种做法,鉴于其相关的成本高,可以尽量减少使用资讯科技,以维持积极的物流控制。向程度的差异是最小化,物流的生产力将提高。因此,差异减少,消除系统中断,是一个基本的目标,综合物流管理。 库存减少 要达到的目标,库存减少,一个综合物流系统必须控制资产的承诺,并把速度。资产的承诺,是财政的价值部署清单。把速度,反映了利率,这是充实库存随着时间的推移。高转率,再加上预期的库存供货,平均资产用于库存正在迅速而有效利用,这就是整体资产承诺支持一个综合运作减至最低。 库存能够而且确实方便可取的好处这是很重要的要请记住。库存是至关重要的实现规模经济,在制造业和采购。目的是要减少和管理存货,以尽可能最低的水平,同时实现整体供应链绩效的目标。

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低压配电系统的工厂供电课程设计 姓 名 学 号 院、系、部 电气工程系 班 号 完成时间 2012年6月18日 ※※※※※※※※※ ※ ※ ※ ※ ※ ※ 2009级 工厂供电课程设计

设计任务书 一、设计内容: (1)由总降压变电所的配出电压和用电设备的电压要求,参考国际规定的标准电压等级确定车间变电所的电压级别。 (2)计算负荷采用需用的系数法,计算出单台设备支线、用电设备组干线和车间变电所低压母线和进线的计算负荷。 (3)由计算负荷结果,确定补偿方式,计算出补偿容量,选择电容器个数和电容柜个数。 (4)按对负荷可靠性要求,确定车间变电所电气主接线。 (5)按车间变电所低压母线的计算负荷,确定变电器的容量和台数。 (6)导线截面积的选择,支线和干线按发热条件选择,进线电缆按经济电缆密度选择,按允许发热,电压损耗进行校验。 (7)短路电流计算,绘制计算电路和等值电路图,确定短路点,计算出各短路点短路电流值及短路容量。 (8)车间变电所低压母线按发热条件选择,按短路的热合力校验。 (9)按国家规定的标准符号和图符,用CAD画出车间变电所的电气主接线图、车间配电系统和配电平面图。 二、设计条件: (1)机加车间符合全部为三级负荷,对供电可靠性要求不高。

(2)车间平面布置图如下图所示 (3)车间电气设备各细表如下表所示 设备代号设备名称台数单台容量(kW)效率功率因数启动倍数备注1~3 普通车床C630-1 3 7.6 0.88 0.81 6 4 内圆磨床M2120 1 7.2 5 0.88 0.83 6 5,16 砂轮机S3SL-300 2 1.5 0.92 0.82 6.5 6 平面磨床M7130 1 7.6 0.88 0.82 6 7~9 牛头刨床B6050 3 4 0.87 0.82 6 11,12 普通车床C6140 2 6.125 0.89 0.81 6 13~15 普通车床C616 3 4.6 0.90 0.81 6 17,18 单臂龙门刨床B1012 2 67.8 0.86 0.81 2.5 19 龙门刨床B2016 1 66.8 0.86 0.81 2.5 20,21 普通车床C630 2 10.125 0.88 0.81 6 22 立式钻床Z535 1 4.625 0.90 0.80 6 23 立式车床C534J1 1 80 0.86 0.80 3 24 摇臂钻床Z35 1 8.5 0.87 0.82 5.5

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英文原文 Introductions to Control Systems Automatic control has played a vital role in the advancement of engineering and science. In addition to its extreme importance in space-vehicle, missile-guidance, and aircraft-piloting systems, etc, automatic control has become an important and integral part of modern manufacturing and industrial processes. For example, automatic control is essential in such industrial operations as controlling pressure, temperature, humidity, viscosity, and flow in the process industries; tooling, handling, and assembling mechanical parts in the manufacturing industries, among many others. Since advances in the theory and practice of automatic control provide means for attaining optimal performance of dynamic systems, improve the quality and lower the cost of production, expand the production rate, relieve the drudgery of many routine, repetitive manual operations etc, most engineers and scientists must now have a good understanding of this field. The first significant work in automatic control was James Watt’s centrifugal governor for the speed control of a steam engine in the eighteenth century. Other significant works in the early stages of development of control theory were due to Minorsky, Hazen, and Nyquist, among many others. In 1922 Minorsky worked on automatic controllers for steering ships and showed how stability could be determined by the differential equations describing the system. In 1934 Hazen, who introduced the term “ervomechanisms”for position control systems, discussed design of relay servomechanisms capable of closely following a changing input. During the decade of the 1940’s, frequency-response methods made it possible for engineers to design linear feedback control systems that satisfied performance requirements. From the end of the 1940’s to early 1950’s, the root-locus method in control system design was fully developed. The frequency-response and the root-locus methods, which are the

外文翻译中文版

铝、钙对熔融铁的复合脱氧平衡 天鸷田口,秀ONO-NAKAZATO,Tateo USUI,Katsukiyo MARUKAWA,肯KATOGI和Hiroaki KOSAKA。 研究生和JSPS研究员, 工程研究院,大阪大学,2-1山田丘, 吹田,大阪565 - 0871日本。 1)材料科学与工程课程,材料科学和制造分支,工程研究院,大阪大学, 2-1山田丘, 吹田, 大阪565 - 0871日本。 2)高端科技创新中心、大阪大学,2-1山田丘,吹田,大阪565 - 0871日本。 3)Electro-Nite贺利日本,有限公司,1-7-40三岛江,高槻,大阪569 - 0835日本。 4)TOYO工程研究中心有限公司,2-2-1春日,茨城,大阪567 - 0031日本。 (发表2005年6月17日,刊发于2005年7月20日) 氧夹杂对钢液的炼钢反应的影响是很显著的,例如脱硫。控制钢液氧含量是很重要的。使用良好的脱氧剂(如铝、钙),有效减少钢液的氧含量。研究者已经在复合脱氧方面做了一些探究。然而,实验数据不完全符合热力学数据计算值。因为没有具体可以利用的熔融铁钙脱氧的确切热力学数据。在本研究中,铝、钙对熔融铁的复合脱氧平衡控制在1873K。Al-Ca在熔铁脱氧中氧活度通过测量电动势(EMF)的方法求得。Al-Ca复合脱氧平衡实验的有效性由过去的和现在的研究结果共同综合判断的,本实验的Al-Ca脱氧平衡能够比过去的研究更好地反应Fe-Al-Ca-O系的关系。 关键词:复合脱氧,铝合金,钙,氧活度,电动势方法,炼钢,生石灰,氧化铝。 1前言 近年来,随着对超洁净钢的要求越来越高,需要更严格地控制钢中夹杂物。降低和控制钢中夹杂物含量在几个ppm以内。特别地,氧夹杂在钢液炼钢反应中的影响(例如脱硫)是非常大的,控制钢液中氧含量是非常重要的。使用强脱氧剂(如铝、钙)有效降低钢液的氧含量。Al-Ca复合脱氧是更有效的,已经做了一些关于复合脱氧的实验。然而,实验结果不完全符合热力学计算值,因为钙在熔铁脱氧平衡的热力学数据被认为由于测量困难是不可靠的。基于这个

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