Intelligent Recognition Using Ultralight Multifunctional Nano‑Layered Carbon Aerogel Sensors with Human‑Like Tactile Perception

Humans can perceive our complex world through multi-sensory fusion.Under limited visual conditions,people can sense a variety of tactile signals to identify objects accurately and rapidly.However,replicating this unique capability in robots remains a significant challenge.Here,we present a new form of ultralight multifunctional tactile nano-layered carbon aerogel sensor that provides pressure,temperature,material recognition and 3D location capabilities,which is combined with multimodal supervised learning algorithms for object recognition.The sensor exhibits human-like pressure(0.04–100 kPa)and temperature(21.5–66.2℃)detection,millisecond response times(11 ms),a pressure sensitivity of 92.22 kPa^(−1)and triboelectric durability of over 6000 cycles.The devised algorithm has universality and can accommodate a range of application scenarios.The tactile system can identify common foods in a kitchen scene with 94.63%accuracy and explore the topographic and geomorphic features of a Mars scene with 100%accuracy.This sensing approach empowers robots with versatile tactile perception to advance future society toward heightened sensing,recognition and intelligence.

Mechanoluminescent-Triboelectric Bimodal Sensors for Self-Powered Sensing and Intelligent Control

Self-powered flexible devices with skin-like multiple sensing ability have attracted great attentions due to their broad applications in the Internet of Things(IoT).Various methods have been proposed to enhance mechano-optic or electric performance of the flexible devices;however,it remains challenging to realize the display and accurate recognition of motion trajectories for intelligent control.Here,we present a fully self-powered mechanoluminescent-triboelectric bimodal sensor based on micronanostructured mechanoluminescent elastomer,which can patterned-display the force trajectories.The deformable liquid metals used as stretchable electrode make the stress transfer stable through overall device to achieve outstanding mechanoluminescence(with a gray value of 107 under a stimulus force as low as 0.3 N and more than 2000 cycles reproducibility).Moreover,a microstructured surface is constructed which endows the resulted composite with significantly improved triboelectric performances(voltage increases from 8 to 24 V).Based on the excellent bimodal sensing performances and durability of the obtained composite,a highly reliable intelligent control system by machine learning has been developed for controlling trolley,providing an approach for advanced visual interaction devices and smart wearable electronics in the future IoT era.

Application of Zero-Watermarking for Medical Image in Intelligent Sensor Network Security

The field of healthcare is considered to be the most promising application of intelligent sensor networks.However,the security and privacy protection ofmedical images collected by intelligent sensor networks is a hot problem that has attracted more and more attention.Fortunately,digital watermarking provides an effective method to solve this problem.In order to improve the robustness of the medical image watermarking scheme,in this paper,we propose a novel zero-watermarking algorithm with the integer wavelet transform(IWT),Schur decomposition and image block energy.Specifically,we first use IWT to extract low-frequency information and divide them into non-overlapping blocks,then we decompose the sub-blocks by Schur decomposition.After that,the feature matrix is constructed according to the relationship between the image block energy and the whole image energy.At the same time,we encrypt watermarking with the logistic chaotic position scrambling.Finally,the zero-watermarking is obtained by XOR operation with the encrypted watermarking.Three indexes of peak signal-to-noise ratio,normalization coefficient(NC)and the bit error rate(BER)are used to evaluate the robustness of the algorithm.According to the experimental results,most of the NC values are around 0.9 under various attacks,while the BER values are very close to 0.These experimental results show that the proposed algorithm is more robust than the existing zero-watermarking methods,which indicates it is more suitable for medical image privacy and security protection.

Modeling of Sensor Enabled IrrigationManagement for Intelligent Agriculture Using Hybrid Deep Belief Network

Artificial intelligence(AI)technologies and sensors have recently received significant interest in intellectual agriculture.Accelerating the application of AI technologies and agriculture sensors in intellectual agriculture is urgently required for the growth of modern agriculture and will help promote smart agriculture.Automatic irrigation scheduling systems were highly required in the agricultural field due to their capability to manage and save water deficit irrigation techniques.Automatic learning systems devise an alternative to conventional irrigation management through the automatic elaboration of predictions related to the learning of an agronomist.With this motivation,this study develops a modified black widow optimization with a deep belief network-based smart irrigation system(MBWODBN-SIS)for intelligent agriculture.The MBWODBN-SIS algorithm primarily enables the Internet of Things(IoT)based sensors to collect data forwarded to the cloud server for examination purposes.Besides,the MBWODBN-SIS technique applies the deep belief network(DBN)model for different types of irrigation classification:average,high needed,highly not needed,and not needed.The MBWO algorithm is used for the hyperparameter tuning process.A wideranging experiment was conducted,and the comparison study stated the enhanced outcomes of the MBWODBN-SIS approach to other DL models with maximum accuracy of 95.73%.

The application of intelligent sensors in medical research:a review

The rapid advancement of biomedicine in the twenty-first century has been facilitated by the constant innovation in biomedical technology.The most crucial issue in the field of medicine is to use sensor technology to gather information from primitive organisms,particularly the human body.Design,development,and application of biomedical sensors in the study of clinical diseases’diagnosis and therapy have all been significantly aided by the advancement of medicine.The interest in creating sensors significantly increased in the 1960s.Chemical and biological sensors have been swiftly created in response to an urgent practical necessity,enabling the creation of selective sensors for the direct detection of diverse ions and compounds.The traditional large-size sensors are quickly turning into miniature sensors and are rapidly applied in biological and medical fields.Currently,wearable electronic blood pressure monitors,home blood glucose meters,and quick body surface digital thermometers are commonly used.The advent of a wide variety of medical-grade wearable sensors that will enable real-time biometric data tracking of a large range of physiological characteristics will likely be one of the most revolutionary,exciting,and difficult changes to come to medicine over the next several years.For possible uses in the entertainment,health monitoring,and medical care industries,high-performance flexible strain sensors connected to clothing or human skin are necessary.The use of sensors in the development of biomedical diagnostic tools and medical equipment will enhance human quality of life in the twenty-first century.This article will introduce the current medical sensor field related to sensors for physical quantities,sensors for chemical quantities,sensors for biological quantities such as electronic nose,electronic tongue,and their applications.

Multidiscipline Applications of Triboelectric Nanogenerators for the Intelligent Era of Internet of Things

In the era of 5G and the Internet of things(IoTs),vari-ous human-computer interaction systems based on the integration of triboelectric nanogenerators(TENGs)and IoTs technologies dem-onstrate the feasibility of sustainable and self-powered functional systems.The rapid development of intelligent applications of IoTs based on TENGs mainly relies on supplying the harvested mechanical energy from surroundings and implementing active sensing,which have greatly changed the way of human production and daily life.This review mainly introduced the TENG applications in multidisci-pline scenarios of IoTs,including smart agriculture,smart industry,smart city,emergency monitoring,and machine learning-assisted artificial intelligence applications.The challenges and future research directions of TENG toward IoTs have also been proposed.The exten-sive developments and applications of TENG will push forward the IoTs into an energy autonomy fashion.

Intelligent Deep Learning Enabled Wild Forest Fire Detection System

The latest advancements in computer vision and deep learning(DL)techniques pave the way to design novel tools for the detection and monitoring of forestfires.In this view,this paper presents an intelligent wild forestfire detec-tion and alarming system using deep learning(IWFFDA-DL)model.The pro-posed IWFFDA-DL technique aims to identify forestfires at earlier stages through integrated sensors.The proposed IWFFDA-DL system includes an Inte-grated sensor system(ISS)combining an array of sensors that acts as the major input source that helps to forecast thefire.Then,the attention based convolution neural network with bidirectional long short term memory(ACNN-BLSTM)model is applied to examine and identify the existence of danger.For hyperpara-meter tuning of the ACNN-BLSTM model,the bacterial foraging optimization(BFO)algorithm is employed and thereby enhances the detection performance.Finally,when thefire is detected,the Global System for Mobiles(GSM)modem transmits messages to the authorities to take required actions.An extensive set of simulations were performed and the results are investigated interms of several aspects.The obtained results highlight the betterment of the IWFFDA-DL techni-que interms of various measures.

APPLICATION OF FEA TO THE COLLOCATION OF ACTUATOR/SENSOR IN THE INTELLIGENT STRUCTURES

The piezothermoelectric actuator/sensor collocation for advanced intelligent structure is studied. The quasi-static equations of piezothermoelasticity are used to analyze the coupling effects between the displacement, temperature and electric fields of piezothermoelasticity continua and the governing equations for piezothermoelasticity continua are derived to discuss the effects of coupling factors on the control/sensing performance in intelligent structure. Based on those analyses, a finite element analysis model of distributed piezothertnoelectric continua is developed later. The thermal stress and deformation of a beam are calculated by FEA method so as to determine the optimal actuator/sensor placement. Based on the results of the optimal analysis procedure of actuator/sensor placement, some conclusions of actuator/sensor placement are obtained. Thus, the optimal actuator/sensor placement for piezothermoelectric intelligent structure can be found from the actuator/sensor placements available so that intelligent system will have the best controllability and observability.

Building an Intelligent Home Space for Service Robot Based on Multi-Pattern Information Model and Wireless Sensor Networks

This paper is concerned with constructing a prototype intelligent home environment for home service robot. In this environment, multi-pattern information can be represented by some intelligent artificial marks. Light-packs service robots can provide reliable and intelligent service by interacting with the environment through the wireless sensor networks. The intelligent space consists the following main components: smart devices with intelligent artificial mark;home server that connects the smart device and maintains the information through wireless sensor network;and the service robot that perform tasks in collaboration with the environment. In this paper, the multi-pattern information model is built, the construction of wireless sensor networks is presented, the smart and agilely home service is introduced. Fi- nally, the future direction of intelligent space system is discussed.

The ZigBee Based Wireless Sensor and Actor Network in Intelligent Space Oriented to Home Service Robot

In the study of intelligent space oriented to home service robot, an important technology is how to construct an communication network which has the characters of high reliability and easy building. In this paper, based on the characteristics of ZigBee protocol, ZigBee technology is used to construct a wireless sensor and actor network. Several intelligent services based on ZigBee wireless sensor and actor network are shown to certify the reliability of this communication network. ZigBee wireless sensor and actor network builds an information bridge for the components in the intelligent space, the spatially distributed devices are connected together seamlessly. With this network, robot can share the mass information in the intelligent space and improve its performance with 'light-packs', devices in intelligent space, such as lamp, curtain can be controlled autonomously.

Zigbee Based Wireless Sensor and Actuator Network for Service Robot Intelligent Space

Wireless sensor and actuator network is the key technology of service robot intelligent space. This paper is concerned with design and implementation of a ZigBee based wireless sensor and actuator network (hereinafter referred to as ZWSAN), which has been applied in our service robot intelligent space successfully. Firstly, a simplified ZigBee stack applied to ZWSAN is proposed and the primitives of the stack are illustrated after a short overview of ZigBee protocols. Then the implementation of hardware module and software stack is introduced in detail as well as several representative devices integrated into ZWSAN, including environmental sensors for environmental perception, home devices controllers for device control, embedded speech recognition module for speech control, IMU module for abnormal behaviors detection and laser robot control for service robot navigation. An application example is described to demonstrate how the devices in ZWSAN to provide service cooperatively. Finally, we conclude this paper and discuss the future directions.

Intelligent 3-Way Priority-Driven Traffic Light Control System for Emergency Vehicles

The problem of traffic congestion is a significant phenomenon that has had a substantial impact on the transportation system within the country. This phenomenon has given rise to numerous intricacies, particularly in instances where emergency situations occur at traffic light intersections that are consistently congested with a high volume of vehicles. This implementation of a traffic light controller system is designed with the intention of addressing this problem. The purpose of the system was to facilitate the operation of a 3-way traffic control light and provide priority to emergency vehicles using a Radio Frequency Identification (RFID) sensor and Reduced Instruction Set Computing (RISC) Architecture Based Microcontroller. This research work involved designing a system to mitigate the occurrence of accidents commonly observed at traffic light intersections, where vehicles often need to maneuver in order to make way for emergency vehicles following a designated route. The research effectively achieved the analysis, simulation and implementation of wireless communication devices for traffic light control. The implemented prototype utilizes RFID transmission, operates in conjunction with the sequential mode of traffic lights to alter the traffic light sequence accordingly and reverts the traffic lights back to their normal sequence after the emergency vehicle has passed the traffic lights.

Resource Allocation for IRS Assistedmm Wave Wireless Powered Sensor Networks with User Cooperation

In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.

Study of Detecting Impact Damage for Composite Material Based on Intelligent Sensor

A system of impact damage detection for composite material structures by using an intelligent sensor embedded in composite material is described. In the course of signal processing, wavelet transform has the exceptional property of temporal frequency localization, whereas Kohonen artificial neural networks have excellent characteristics of self-learning and fault-tolerance. By combining the merits of abstracting time-frequency domain eigenvalues and improving the ratio of signal to noise in this system, impact damage in composite material can be properly recognized.

Management of Intelligent Campus Wireless Sensor Networks Based on Runtime Model

To quick customize and develop intelligent campus internet of things (ICIOT) system more efficiently, in this paper an approach based on runtime model to managing intelligent campus wireless sensor networks is proposed. Firstly, manageability of intelligent campus wireless sensors is abstracted as runtime models which automatically and immediately propagate any observable runtime changes of target resources to corresponding architecture models. Then, a composite model of intelligent campus wireless sensors is constructed through merging their runtime models in order to manage different kinds of devices in a unified way. Finally, a customized model is constructed according to the personalized management requirement and the synchronization between the customized model and the composite model is ensured through model transformation. Thus, all the management tasks can be carried through executing operating programs on the customized model. In the part of the teaching area schools conducted experiments and compared with the traditional method, this method can be more effective management of campus facilities, more energy efficient and orderly, which can reach a 16.7% energy saving.

Review on the Sensor Technology Applied in the Intelligent Learning Environment

The development of sensor technology promotes the transformation of the intelligent learning environment. Through the research of the sensor technology application, this paper described the intelligent learning environment application system of the sensor technology and the management functions, conference organization, a library building, information collection, monitoring and equipment sharing function the role of sensor technology played in the intelligent learning environment.

The Implementation of Electronic Intelligent Tag System Based on Wireless Sensor Network

Recently, Wireless Sensor Network (WSN) has been widely applied in many fields. In this paper, we design and implement a WSN-based Electronic Intelligent Tag System (EITS) to provide intelligent management of the modern supermarkets. As a main transceiver, nRF24L01+ wireless module is used in this system, which will make it possible to achieve low-power and low-cost for EITS. This system fully embodies the advantages and characteristics of WSN. This paper will introduce the system architecture, hardware structure and software design in details;and put forward a specific solution. Finally, we achieve the intelligent management of the mall based on wireless sensor network technology.

A Review on Mobile and Sensor Networks Innovations in Intelligent Transportation Systems

Rapid developments of mobile technologies, data acquisition and big data analytics, and their integration with critical application domains such as transportation systems have the potential to produce more efficient, real-time, intelligent and safe transportation infrastructure. To increase the quality of transportation services, wireless sensor networks, mobile phones, crowd sourcing, RFID and Bluetooth technologies are being used. We surveyed innovations that were transformed from ideas in research labs into commercial systems in practical use. In this paper, we present some innovative mobile technologies, services and platforms that are being used in modern transportation applications including traffic data acquisition, traffic management and control, route optimizations, infrastructure redesign, road safety and enhancing user experience.

Provisioning Intelligent Water Wave Optimization Approach for Underwater Acoustic Wireless Sensor Networks

In the Acoustics channel,it is incredibly challenging to offer data transfer for time-sourced applications in an energy-efficient manner due to higher error rate and propagation delay.Subsequently,conventional re-transmission over any failure generally initiates significantly larger end-to-end delay,and therefore it is not probable for time-based services.Moreover,standard techniques without any re-transmission consume enormous energy.This investigation proposes a novel multi-hop energy-aware transmission-based intelligent water wave optimization strategy.It ensures reduced end-to-end while attaining potential amongst overall energy efficiency end-to-end packet delay.It merges a naturally inspired meta-heuristic approach with multi-hop routing for data packets to reach the destination.The appropriate design of this Meta heuristic-based energy-aware scheme consumes lesser energy than the conventional one-hop transmission strategy without re-transmission.However,there is no hop-by-hop re-transmission facilitated.The proposed model shows only lesser delay than conventional methods with re-transmission.This work facilitates extensive work to carry out the proposed model performance with the MATLAB simulation environment.The results illustrate that the model is exceptionally energyefficient with lesser packet delays.With 500 nodes,the packet delivery ratio of proposed model is 100%,average delay is reduced by 2%,total energy consumption is 8 J,average packet redundancy is 1.856,and idle energy is 6.9Mwh.The proposed model outperforms existing approaches like OSF,AOR,and DMR respectively.

Introducing Intelligent Agents Potential into a competent Integral Multi-Agent Sensor Network Simulation Architecture Design

During this research we spot several key issues concerning WSN design process and how to introduce intelligence in the motes. Due to the nature of these networks, debugging after deployment is unrealistic, thus an efficient testing method is required. WSN simulators perform the task, but still code implementing mote sensing and RF behaviour consists of layered and/or interacting protocols that for the sake of designing accuracy are tested working as a whole, running on specific hardware. Simulators that provide cross layer simulation and hardware emulation options may be regarded as the last milestone of the WSN design process. Especially mechanisms for introducing intelligence into the WSN decision making process but in the simulation level is an important aspect not tackled so far in the literature at all. The herein proposed multi-agent simulation architecture aims at designing a novel WSN simulation system independent of specific hardware platforms but taking into account all hardware entities and events for testing and analysing the behaviour of a realistic WSN system. Moreover, the design herein outlined involves the basic mechanisms, with regards to memory and data management, towards Prolog interpreter implementation in the simulation level.