107results about How to "Self-organizing" patented technology

The invention belongs to the field of intelligent household, relates to an intelligent household control system, and particularly to an intelligent household control system based on ZigBee and cloud computing. A main structure includes an information acquisition and equipment control module, a ZigBee wireless sensing network, a household intelligent gateway, an RFID device, a cloud server, and a mobile terminal device, the information acquisition and equipment control module includes an environment information acquisition sensor and a household equipment controller, a ZigBee coordinator node, a ZigBee router node, and a ZigBee terminal node form a ZigBee three-level tree-shaped wireless sensing network to form an intelligent household network frame. The ZigBee network performs the intelligent regulation and control on the household equipment, the user data is stored and processed via the cloud server, the users' behavior habit is deeply tapped, so that a household control scheme based on the users' behavior habit is generated, the indoor wireless signal radiation maintains at a low level, the main structure is simple, the design conception is ingenious, the application environment is friendly, and the market prospect is wide.

The invention discloses a method for improving a BP (back propagation) neutral network and based on a genetic algorithm. The method includes coding the BP network to determine structure of the neutral network, wherein the structure includes the number of hidden layers and the number of units of each layer; adopting real-number coding to code by taking weight and threshold as genes, wherein each neutral network corresponds to a chromosome after coding; using the genetic algorithm to perform selection optimization on the network, wherein selection optimization includes the steps of selection, crossing and variation; training the BP network to acquire a final result; decoding an optimal individual selected by the genetic algorithm to generate a new neutral network, and training the new network by applying a BP training algorithm to acquire a final result. The method combines the genetic algorithm with the BP network, thereby being capable of fully utilizing advantages of the both, the problem that initial weight and threshold of the BP network are difficult to determine can be solved, searching range can be narrowed, training speed of the BP network can be increased, and the problem of local minimum can be improved.

The invention relates to a motor rotating-speed tracking control method based on a self-adaptive fuzzy neural network, wherein rotating-speed and current double closed-loop control is adopted, an outer ring is a rotating-speed ring, a sliding-mode control theory-based fuzzy neural-network controller (SMFNN) is designed, an inner ring is a current ring, and a PI (Proportional-Integral) controller is adopted; a fuzzy neural-network rotating-speed controller comprises two parts, wherein one part is a PID (Proportional-Integral-Derivative) controller, and the other part is the fuzzy neural network, online real-time learning is carried out through the fuzzy neural network by utilizing a parameter correcting method designed on the basis of the sliding-mode control theory, and the two parts jointly act to obtain the output ir of the rotating-speed controller, i.e. a difference obtained by subtracting the output iFNN of the fuzzy neural network from the output iPID of the PID controller is used as the output ir of the rotating-speed controller. The control precision and the anti-interference performance of a motor speed-adjusting system can be improved through the control strategy of the motor rotating-speed tracking control method.

The invention discloses an ant colony optimization processing method of large-scale multi-target intelligent moving route selection; after data of NTSP target logistics delivery addresses, distances between every two addresses, and M price of cost for passing through each route are obtained, a route planning unit is solved by ant colony optimization technology so as to obtain a specific walking route for intelligent mobile-agent delivery, and the route is outputted to an executive mechanism for realization. When the method is used to solve the problem of large-scale multi-target intelligent moving route selection, the invention has good optimization performance, and has the advantages of parallelism, self-organization, strong robustness, and the like, and the obtained solutions are large in quantity, high in quality, and have strong approximation capability to the real Pareto solution set; the obtained solution set has uniform distribution; the calculation speed is high. The inventioncan be used in intelligent processing units of route planning systems in fields of logistics distribution, intelligent traffic, internet, robots, etc.

A port on-site data acquiring, transmitting, sending and issuring system based on zigbee technology in the remote monitoring and controlling field of electromechanical equipment, comprises a wireless sensing network and a remote data server, wherein the wireless sensing network is distributed in a port working field, and can acquire working state data of the port field, collect the intra-network acquired data in a zigbee wireless manner, pack the collected data, and transmit to the remote data server via wired enterprise in-house network based on a transmission control protocol and an internetwork protocol. The remote data server can receive the data based on the transmission control protocol and the internetwork protocol, resolve the data according to the packed data transmission format, store the data in a database, and issue the data in a web service mode. The invention provides data support for monitoring application program development, failure pre-warning and equipment maintenance. In addition, the low-cost zigbee technology can reduce system complexity, and has good anti-interference performance, expandability and practicability.

The invention discloses a building load forecasting method and device based on an improved IHCMAC (Hyperball Cerebellar Model Articulation Controller) neural network model. The method comprises the steps of: simulating the actual operation of a building to obtain building cold / heat load data and influencing factor data; determining input variables of the model according to the degree of correlation between the influencing factors and the building cold / heat load; clustering the input variables according to a particle swarm-K mean clustering algorithm to obtain values of L clustering centers, i.e., model node values, and defining a Gaussian kernel function for each node; and updating the weights of the nodes via a weight training algorithm to obtain a building load forecasting value of the model. The method has the advantages of fast convergence, high learning precision and strong generalization ability, and can provide a decision basis for energy-saving optimization control of a building system.

The present invention relates to an OPC UA data service gateway device and an implementation method thereof. The method and device are used for realizing an embedded OPC UA server in the condition of applying industry-standard communication protocol OPC UA, the related information data of different types of field equipment such as an instrument and a PLC can be collected periodically, the equipment is mapped to an OPC UA address space, corresponding equipment model and equipment relation model are established, and the identification and management of the field equipment are realized. At the same time, in order to achieve the interaction between an OPC UA client and the server, an OPC UA transaction management mechanism is applied, and thus the OPC UA server can provide monitoring, listening, inquiring and other services for the client. The invention aims to use an OPC UA protocol to realize an equipment interface technique with the support of multiple wireless communication protocol standards, service adapter hardware with low power consumption and easy expansion is used as a carrier, and thus the underlying protocol and implementation are not considered in carrying out automatic control.

The invention relates to a roof green insulation system and a method thereof, which belong to the field of building roof green insulation. The green insulation system comprises a cement mortar screeding basal plane layer 2, an adhesive mortar layer 3, an insulation board layer 4, a finishing layer 5, a self-organizing waterproof sealant 6, a waterproof layer 7, a moisturizing blanket 8, a storage and drainage plate 9, a filter cloth 10, planting soil 11 and a green plant12 upwards from a building roof concrete roof 1 in sequence. The system is suitable for being arranged on a roof of a building or a top slab of a substructure, has the advantage of simple structure, has the functions of thermal insulation, water resistance and greening, effectively protects the building roof, not only can prolong the service life, but also can effectively solve the problem of roof leakage of the building.

The invention discloses a remote-sensing image variation detecting method based on slow characteristic analysis. A slow characteristic analysis approach is introduced in the detection of multi-temporal remote-sensing image variations; in the slow characteristic analysis approach, the space corresponding relation between the multi-temporal remote-sensing images is completely taken into account, and the original theory aiming at continuous signal analysis is developed into a variation detecting algorithm based on a discrete data set. By utilizing the slow characteristic analysis approach, invariant characteristics can be extracted from a multi-temporal remote-sensing image data set to serve as a characteristic space; in the characteristic space, the spectrum difference between the multi-temporal remote-sensing images is restrained, and true variation is highlighted, so that the variation detection accuracy can be enhanced. The slow characteristic analysis approach is simple to perform and high in arithmetic speed.

The invention discloses a wireless-network-based water gate security monitoring system, belonging to the field of security monitoring of water transport engineering. The wireless-network-based water gate security monitoring system comprises a data acquisition system, a data transmission system and a remote monitoring scheduling system, wherein the data acquisition system comprises a parameter acquisition node, a video acquisition node, a route node and a coordinator node, and the remote monitoring scheduling system comprises a database server system and a monitoring scheduling center. According to the invention, a wireless acquisition technology and a wireless transmission technology are adopted to carry out acquisition, transmission, processing, display, control and other operation on environment parameters, structural parameters and video data of a water gate, and a gate is opened and closed according to an operating instruction. According to the invention, a wireless sensor network technology, a third generation wireless communication technology and a video monitoring technology are applied to water gate management, all the operations from information acquisition, transmission and storage to information processing are carried out in digital information image forms, and thus, the efficiency and the security in water gate management are greatly increased.

The invention relates to a working method for a satellite communication system based on single channel single carrier time division multiple access, which comprises the following operating steps: (1) when a satellite communication network is established initially, all ground base stations compete for a temporary centre base station which acquires the information of the ground base stations of thenetwork in a mode of calling the name, and when calling the name, all the ground base stations adopt a competition mode to finish the response of calling the name; (2) the temporary centre base station elects the optimal centre base station of the current network according to the information of all the ground base stations in the network; (3) the temporary centre base station delivers controllingright and the information of the ground base stations to the centre base station at the same time; and (4) the centre base station manages the space-time link resources of the whole satellite network, and controls the network to operate normally as follows: the centre base station firstly distributes TDMA frame slot time, and performs the respective keep-alive control together with the common ground base station; and the centre base station also comprises all the controlling operations such as the distribution of data slot time, the addition of new ground base station and the departure of theground base station.

The invention relates to a design method for a multi-target cooperative sampling scheme of randomly-distributed geographic elements, which includes the steps: 1 selecting multiple geographic elements with random distribution characteristics as sampling targets, and acquiring pre-sampling sample point data of the targets; 2 exploring spatial variation structures of the pre-sampling data by an ordinary Kriging method, fitting and generating a theory semi-variable function of each target, and obtaining a spatial distribution integral of all the targets by a Gaussian sequential random simulation method according to the theory semi-variable functions and the pre-sampling sample point data in the step 1; 3 computing the minimum cooperative sample size according to the precision requirements of the targets and prior variance, and setting a cooperative particle swarm optimization parameter; and 4 optimizing a current pre-sampling sample point scheme by means of cooperative particle swarm optimization, so that the multi-target cooperative sampling scheme is obtained. By the aid of the method, on-site sampling cost can be saved, self-organization and optimization during distribution of thesampling sample points are improved, and the design efficiency of the multi-target cooperative sampling scheme of the geographic elements is enhanced.

The invention discloses a photovoltaic grid-connected inverter and a control method of the photovoltaic grid-connected inverter. The photovoltaic grid-connected inverter comprises a maximum power point tracking module, a power switch tube object, an equivalent filter, a phase-locked loop, an electric grid disturbance measurement module, a current transducer, a voltage transducer and a BP (Back Propagation) nerve network control module, wherein the output end of the voltage transducer is connected to the input end of the phase-locked loop; the BP nerve network control module is respectively connected with the output end of the maximum power point tracking module and the phase-locked loop, the output end of the electric grid disturbance measurement module and the output end of the current transducer, which are used as three input ends of the BP nerve network control module; the output end of the BP nerve network control module is connected with the input end of the power switch tube object; and the output end of the power switch tube object is connected with the input end of the equivalent filter. The photovoltaic grid-connected inverter is higher in intelligent and output precision and is capable of adapting various electric grid environments and improving the stability and the reliability of a photovoltaic grid-connected power generation system.

The invention discloses a pressurized water reactor (PWR) nuclear power plant reactor core power model predictive control method based on a genetic algorithm. The method comprises the steps of establishing a mathematical state space model of a reactor core; linearizing the mathematical state space model of the reactor core; establishing a power predictive control model of the reactor core; and carrying out parameters setting for the power predictive control model based on a genetic algorithm. The invention combines operating parameters of the PWR core, sets the parameters in a controller by using an improved genetic algorithm, obtains a global optimal solution, and achieves self-adaptive adjustment of PWR nuclear power plant reactor core power control; also predicts a future deviation value by using the predictive model, determines a current optimal control strategy by rolling optimization, and enables minimum deviation between a future controlled variable and a value of expectation; and optimizes undetermined parameters in the reactor core power predictive control model by using the genetic algorithm, and obtains optimal values for the undetermined parameters.

The invention relates to a distributed transient electromagnetic data acquisition system based on a wireless sensor network. The distributed transient electromagnetic data acquisition system is composed of an industrial personal computer, a coordinator, a plurality of router nodes, a plurality of terminal acquisition nodes and the wireless sensor network serving as a basic network, wherein the router nodes and the terminal acquisition nodes are distributed flexibly. The industrial personal computer is connected with the coordinator through a USB, and the terminal acquisition nodes, the router nodes and all nodes of the coordinator are in wireless connection with one another; the terminal acquisition nodes are used for completing acquisition and uploading of transient electromagnetic data; the router nodes are used for completing the router addressing and data forwarding function; the coordinator is used for completing storage, display and USB communication of the acquired data; the industrial personal computer is used for controlling the acquisition process of each node, displaying the data, and completing calculation of obtained data exploration parameters. The distributed transient electromagnetic data acquisition system has high exploration accuracy, connection wires between the nodes are omitted, field operation is convenient, work efficiency is improved, modular design is adopted for the nodes, and maintenance and replacement are convenient.

The invention provides a landslide real-time monitoring system. The system comprises a measurement device, a communication network system and a monitoring computer, wherein the measurement device comprises a linear displacement sensor, a movable strut, a fixed strut, a connecting belt, collectors and the like; the communication network system consists of a ZigBee coordinator with a general packet radio service (GPRS) module and a plurality of ZigBee terminal nodes; the ZigBee coordinate and the ZigBee terminal nodes form a field ZigBee network; and the ZigBee terminal nodes are the collectors in the measurement device. When landslide causes surface displacement, the length of the connecting belt varies, the variation can be measured through the linear displacement sensor, and landslide information collected by the collectors is transmitted to the monitoring computer of a monitoring center through the field ZigBee network. The surface displacement information is acquired by utilizing the linear displacement sensor, so the device has the characteristics of all-weather real-time monitoring, high measurement accuracy and low price.

The invention relates to a road condition real-time collecting system based on wireless sensor network, wherein it comprises detecting center, collecting node, network gate, sensor node, and pure route node; the connecting node and network gate are connected via wire; the network gate and detecting center are connected via internet or special network; the sensor node, pure route node and collecting node are connected via wireless multi-jump network. the invention uses wireless multi-jump communication, to apply network dynamic change, with self-organism, self-manage, self-adaptive properties; each node has sensor function and route function, while the abundant node distribution has high reliability and low cost, etc.

The invention provides a soft-measuring method for density in concentrating process of salvia miltiorrhiza injection production, comprising the following steps: gathering the historical data of each sensor and densimeter in the concentration process of salvia miltiorrhiza, wherein the history data relate to concentrated solution density value and sensor data gathered on line in production process;selecting easily obtained procedure variables including gas phase temperature, liquid phase temperature, pressure and concentrated solution liquid level that have higher degree of correlation with density from each sensor data, and screening representative dataset; using a multivariate analysis method for building a soft-measuring model of density; and gathering the procedure variables on line, and using the soft-measuring model of density to carry out real-time estimation to control the concentration process. Aiming at the problem that the density in the concentration process of salvia miltiorrhiza injection production is difficultly monitored in real time, the invention provides a fast density soft-measuring method with high precision, which makes full use of the history data obtained by each sensor from the production process, and is beneficial to improvement of quality control on salvia miltiorrhiza injection production.

The invention discloses a vehicle positioning method which comprises the following steps: collecting a plurality of training samples as a training set N, and taking a picture with a training area driving environment marker shot by a vehicle camera and a high-precision map of a training area where a vehicle is located when the picture is shot as a sample n in the training set, wherein n belongs toN; adopting a deep learning method, the training set is used for training a model, and a trained model is obtained; when the vehicle enters the prediction area; shooting the driving environment markerin the prediction area to obtain a picture shot in the prediction area, inputting the picture shot in the prediction area and the processed high-precision map which is cached in advance and comprisesthe prediction area into the trained model, and determining the high-precision map of the prediction area where the current vehicle is located; And the current vehicle position coordinate is determined. By the adoption of the method and device, vehicle positioning in the environment where the positioning process does not completely depend on satellite signals and cannot receive the signals can beachieved.

The invention provides a space-frequency-polarization combined cooperation detection method. Considering randomness of a target attitude angle, the method that the largest weighted average detection probability is taken on azimuths is adopted, so that spatial attributes, frequency attributes and polarization attributes of all node radar in a cooperation network are configured, a constructed cooperation detection system can achieve a space-frequency-polarization diversity technology in a combined mode, more and richer target diversified information is obtained in comparison with other radar systems, detection performance is higher, the power range is larger, and furthermore, the mode that a node radar system is combined with a network is adopted, so that the cooperation detection method has the advantages of being resistant to destroying and interfering and achieving self-organization.

The invention discloses an intelligent housing system coordination system and method based on the Zigbee wireless communication technology. The system comprises a main node intelligent housing network controller and housing network devices distributed in rooms respectively. The housing network device in each room comprises a partial node intelligent housing network control router, multiple housing devices, multiple function driving modules used as function executing mechanisms of the housing devices and multiple partial node intelligent housing network controllers. Each housing device is in interactive connection with the corresponding function driving module. Each function driving module is in interactive connection with the corresponding partial node intelligent housing network controller. Each partial node intelligent housing network controller is in communication connection with the corresponding partial node intelligent housing network control router. The Zigbee wireless communication network of the system is formed after the partial node intelligent housing network control routers in the rooms are in communication connection with the main node intelligent housing network controller.

The invention relates to a high-speed data communication method based on a minisatellite cluster ad-hoc network. According to the method, a hybrid network structure is adopted, a minisatellite cluster firstly adopts a centerless ad-hoc network structure, interaction of related information of networking operation control in the cluster is realized, and on the basis, services such routing, route building and control are provided for high-speed transmission of satellite sounding data in the cluster. The hybrid network structure combines advantages of a centerless structure and a centered structure, can realize high-speed transmission of the sounding data in the cluster under the conditions of different mission requirement and different formation configuration, and has a series of advantages of no center, self discovering, automatic configuration, self organization, fault self-recovery, self-adaptive formation changing, high reliability, high availability and the like of a wireless ad-hoc network.

The invention discloses a method of selecting remote sensing video by manual immunity characteristic, its characteristic lies in: (1) opening the remote sensing image; (2) choosing the type area and input parameter; (3) coding and marking characteristic combination, producing the initial immunity unit; (4) decoding and obtaining the sample subset, and calculating saturation; (5) choosing certain immunity from the immunity aggregate to produce immunity aggregate, and recording highest saturation immunity as most matching immunity; (6)judging whether satisfies termination condition, if yes, making most matching immunity to take the optimal solution arithmetic;(7)if not, cloning immunity aggregate;(8) obtaining the variation immune aggregate; (9)calculating the variation immune aggregate saturation;(10) if the candidate immune body kisses with is bigger than most matches the immune aggregate saturation, stores the immunity as candidate immunity aggregate; (11) returning to the step (5), continuing to evolve the immunity aggregate until satisfying the characteristic and choice termination condition.

The invention discloses a sluice safety monitoring system based on a wireless network and belongs to the field of waterway engineering safety monitoring. The sluice safety monitoring system comprises an acquisition system, a data transmission system, a remote monitoring scheduling system. The data acquisition system comprises a parameter acquisition node, a video acquisition node, a routing node and a coordinator node. The remote monitoring scheduling system comprises a database server system and a monitoring scheduling center. An environment parameter, a structure parameter and video data of a sluice are acquired, transmitted, processed, displayed, controlled and the like by the wireless acquisition and wireless transmission technologies, and a sluice gate is opened and closed according to an operating regulation. A wireless sensor network technology, a 3G (third generation) wireless communication network technology and a video monitoring technology are applied to sluice management, operations ranging from information acquisition, transferring, storing to processing are performed by digital information and images, and accordingly efficiency and safety of sluice management are increased greatly.

The invention discloses a transient electromagnetic data acquisition system and method based on a wireless sensor network. The system comprises terminal acquisition nodes, router nodes and a gateway node, wherein a wireless sensor network is formed among the three nodes; the gateway node is connected with an industrial personal computer and receives an instruction of the industrial personal computer and transmits a data acquisition instruction to the terminal acquisition nodes through the wireless sensor network; the terminal acquisition nodes acquire transient electromagnetic data in monitoring areas according to the data acquisition instruction, converts the transient electromagnetic data into digital signals and transmits the digital signals to the gateway node in a data packet form through the wireless sensor network. The distributed transient electromagnetic data acquisition system based on the wireless sensor network has high surveying accuracy, a connecting line between each two nodes is omitted, field operation is convenient, the working efficiency is improved, and the nodes adopt a modular design and are convenient to maintain and replace.

The invention discloses a cutting track planning method for a cantilever type heading machine based on a topological map. The method comprises the following steps: judging a cutting environment according to a tunnel section complex structure identification model, and planning a cutting path and a stop point for exploring a cantilever environment of the heading machine; according to a cutting headpositioning resolving model, resolving the position of the cutting head in the roadway, and constructing a roadway section topological environment map by utilizing an increased neural gas network algorithm; according to the coal roadway cutting rule, an improved ant colony algorithm is utilized, and the shortest path avoiding waste rock inclusion is obtained through planning. In the subsequent section cutting process, if the section environment is obviously changed, the section of the roadway is explored again, meanwhile, a topological map is constructed, and a new optimal cutting track is obtained through planning. By the adoption of the method, the complex and changeable roadway environment can be coped, the optimal track suitable for tunneling is obtained, and therefore autonomous unmanned cutting is achieved step by step.

The invention discloses an urban gas pipe network leakage detecting system based on a centerless ad-hoc network, and relates to the technical field of leakage detection. A gas leakage detecting component is connected with intelligent control nodes. A mobile terminal is connected with the intelligent control nodes. The gas leakage detecting component is arranged above a gas pipeline and is closelyadjacent to the gas pipeline, and the two ends of the gas leakage detecting component extend to the positions of a station, pressure adjusting stations (boxes) and a gate well to be disconnected. Theintelligent control nodes are arranged at the positions of the station, the pressure adjusting stations or the pressure adjusting boxes and the gate well. The mobile terminal achieves human-machine interaction. A valve electric executing device is used for controlling opening and closing of an electromagnetic valve. According to an urban gas pipe network leakage detecting method based on the centerless ad-hoc network, a whole is divided into a plurality of areas, the centerless network is formed, and on the basis of the wavelet analysis and approximate entropy and correlation analysis combination method, detection is conducted. The urban gas pipe network leakage detecting system and method have the beneficial effects that when accidents happen, the fault position information can be rapidlyprepared and calculated according to correlation of gas leakage conveying detection components, and emergency measures are triggered.

The invention relates to a collecting and transmission method for real-time hierarchical nested data of wireless optical fiber sensor networks. The method includes: using central control nodes, routing nodes, control nodes to form a top network in the wireless optical fiber sensor networks, adopting a multi-hop poll mechanism during a top poll period, using the routing nodes and part of the control nodes to implement routing function so as to realize remote multi-hop transmission of control information and sensor data; using the control nodes and wireless optical fiber sensor nodes to form a bottom network, adopting a bisynchronous dynamic time-division multiplexing mechanism during a bottom data collecting and transmission period so as to realize distributed synchronous collecting and transmission of the same hot spots monitoring quantity; and nesting the bottom data collecting and transmission period in the top poll period. The wireless optical fiber sensor networks is low in power consumption, widespread, real-time and the like, and is applicable to known monitoring fields of multiple application environments such as oil depot tank groups, power systems, mine tunnels, greenhouse granaries and the like.

The invention discloses a failure monitoring and self-healing method for a multi-agent combustion gas pipeline based on immune learning. The method comprises following steps: creating a multi-agent system used for monitoring faults of the combustion gas pipeline and self-healing, wherein the multi-agent system contains data collection Agent, immunity Agent, communication Agent, management Agent, assessment Agent and execution Agent; obtaining and analyzing field data of the combustion gas pipeline, utilizing independent component analysis, correlation coefficient and other methods for feature extraction, adopting an immune algorithm to obtain a primary self-healing scheme set, comprehensively analyzing each primary self-healing scheme, selecting the best self-healing scheme according to the size of the comprehensive index and self-restoring failure of the combustion gas pipeline. The failure monitoring and self-healing method for the multi-agent combustion gas pipeline based on immune learning has following beneficial effects: advantages such as openness, transplantability, intelligence, reliability and flexibility are obtained; the self-organization capability, the learning capability and the deduction capability are achieved; and the higher flexibility and robustness are obtained.

The invention discloses a road monitoring system, which comprises a road safety detection module and a monitoring module, wherein the road safety detection module comprises camera acquisition modules, GPS speed measuring modules, weight detection modules, a vehicle distance detection module, a wireless transmitting module and a data processing module; the monitoring module comprises a wireless receiving module, a control module, a display module and a data storage server; the GPS speed measuring modules, the weight detection modules and the camera acquisition modules are sequentially arranged along a driving direction at intervals; a monitoring unit is composed of each GPS speed measuring module, each weight detection module and each camera acquisition module; and when one of the GPS speed measuring modules and one of the weight detection modules acquire abnormal information, the corresponding camera acquisition module is started. The road monitoring system avoids the real-time operation of cameras, prolongs the service life of the cameras, enhances safety, and saves energy.