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Aiming at the problem that it is difficult to obtain the complete and timely device status information of gas-insulated switchgear for traditional methods in deformation monitoring, leading to unable to accurately control the device, which will influence the substation’s safe operation for sure, the paper proposed to use BDS independently developed by China to realize the intelligent detection of the gas-insulated switchgear, and designed a BDS deformation monitoring system for the gas-insulated switchgear of the EHV substation. The experimental result showed that the proposed system could efficiently monitor and pre-warn the deformation of the device.

With the development of Internet of Things (IoT) technology, unattended operation of devices has become an important feature of IoT, which requires devices to perform proper actions to provide services without human intervention. To achieve the unattended operation of IoT, a major challenge is how to accurately predict the actions that the device will perform and meet the personalized requirements of users. To address this challenge, we propose a novel method to predict device status based on the IoT temporal knowledge graph (TKG) and the long short term memory (LSTM) model. We firstly build a TKG for the IoT to provide rich semantic information for the objects and the continuously changing time series data in the IoT. Then, leveraging the advantages of LSTM in sequence learning, the timing characteristics of semantic information in TKG are learned to realize intelligent prediction of the equipment status. To verify the effectiveness of our method, we conducted an experimental verification of device status prediction in a smart home use case, and the experimental results show that our method achieves the state-of-the-art performance.

Poloidal Field Power Supply (PFPS), which consists of twelve independent power supply subsystems, requires large amount of equipment and distributes over a larger area. In order to monitor on-site plant of PFPS in real-time, a distributed on-site real-time monitoring system has been described in this paper. This distributed on-site real-time monitoring system uses Ethernet fieldbus controllers based on Modbus/UDP so that it could achieve the effect of communicating with the PFPS controllers in real-time and the communication cycle would normally be 4 milliseconds. As a result, the distributed on-site real-time monitoring system could collect the device status of onsite plant, control switches on-off, and ability of warning for realtime emergency. All experiments have proved that the on-site real-time monitoring system works successfully and completely meet the requirement of monitoring the PFPS.

This paper describes predictive diagnostics used in a process of telematic systems maintenance focusing on the checkup and potencials for improvements in road tunnel constructions. For this we have chosen the tunnel constructions as the most suitable ones from the telematic systems as they contain huge amount of technologies, systems and subsystems. Tunnel constructions is from its nature complex system providing large amounts of data and many device status and other reports. Actual tunnel status is fundamentally influenced by the operation, the state of technological equipment and, last but not least, by the activity of the operators responding to emergencies, solving normal operation states and planned or operative maintenance. Each part of the tunnel technological equipment requires for its correct operation specific actions, which are planned as a coherent set of rules and operating regulations based on alarms from the technical equipment, evaluation of traffic data and operators' knowledge. This is also applicable to any telematics system that consists of several subsystems or is a larger system based on a distributed diagnostic system.

The network of the secondary system of the smart substation realizes the sharing and interaction of equipment information, and also brings a large amount of secondary system status data. Conventional secondary condition monitoring methods have deficiencies in processing big data. As a research hotspot of artificial intelligence, deep learning has strong data mining capability that meets the needs of state monitoring of smart substation secondary systems. In this context, the paper first outlines the basic ideas of deep learning and the typical structure of several commonly used models. Secondly, the concept, monitoring object and index selection of secondary system monitoring in smart substation are discussed. The advantages and disadvantages of using conventional methods and deep learning in communication network condition monitoring and secondary device status evaluation are then analyzed. Finally, combined with the current research and application status of deep monitoring of secondary system status in smart substation, the future development prospects are prospected.

This paper propose an incentive mechanism to secure large numbers of devices through the use of insurance based on smart contracts. It consists of the automated security evaluation of enterprise IoT devices and the creation of a dynamic insurance premium. To automate the security evaluation of enterprise IoT devices, we collect and store IoT device status data with privacy preservation on blockchain. Then, we track and assess the risk associated with IoT devices with the use of a smart contract. By monitoring this risk over time, we present a means to incentivize the resolution of vulnerabilities by measuring the latent risk in an environment as well as the vigilance of the devices’ managers in resolving these vulnerabilities. In this way, we produce a dynamic cyber insurance premium that more accurately captures the risk profile associated with an environment than existing cyber insurance. Through the use blockchain and smart contracts, this framework also provides public verification for both insured and insurer and provides a level of risk management for the insurer. We also present regulatory considerations in order for this scheme to meet supervisory requirements.

Bluetooth is a universal wireless standard which is used on most smartphones. With the widespread use of Bluetooth on smartphones, Bluetooth security has received a lot of attention, and it is increasingly important to identify and block Bluetooth attacks to ensure that smartphones are free of the threat of Bluetooth attacks. Traditional attack detection techniques are generally based on traffic, and unfortunately smartphone Bluetooth traffic is extremely difficult to capture. Based on this problem, we propose a Bluetooth attack detection method based on device status recognition, which uses the response time of the smartphone to the ping in the Bluetooth L2CAP to remotely monitor the Bluetooth status of the smartphone. Due to the variety of Bluetooth attacks, we can’t easily identify multiple Bluetooth attacks based on response time. For this purpose, we explored the effectiveness of a detection approach based on deep learning. Our experimental results show our algorithm can detect Bluetooth attack with a high precision and high recall.

A proposed solution lies in using methods to ensure the implementation of preventive measures aimed to increase the complexity of implementation of information security threats using a compact device based on a PC/104+ form factor. A counteraction to information attacks is estimated, the device status conditions in various modes and after the introduction of additional protection components are simulated.

Everyday activities and routines should be easy to perform for everyone, including those who are totally blind. This paper introduces a simple audio-based tool aimed at supporting visually-impaired people in checking whether the light in a room is on or off. In this context, we discuss the main issues and considerations for totally blind users with regard to a specific seemingly simple task, which is light detection. The proposed prototype is based on a simple circuit and a form of auditory feedback which informs the user whether they are switching on or off the light. The evaluation conducted by involving blind and sighted people confirmed the usefulness of the proposed tool.

With the development of high-voltage and large-capacity transmission line technology, safe and reliable operation of the transmission line is essential. In view of China’s vast area and varied geographical environment along transmission lines, which are affected by the frequently severe weather and heavy air pollution, etc., it is necessary to detect the device status of the transmission line. Detection equipment and technology should be applied to transmission lines as appropriate to individual lines. State-of-the-art online detection technology and maintenance technology, using infrared and ultraviolet imaging remote sensing, can ensure the safe operation of the line by precisely detecting all kinds of defects of transmission line insulators, conductors, and hardware devices and carrying out line maintenance in good time.

The recent ISO/IEEE 11073 PHD standard presented a way to achieve the communication between personal healthcare devices, but it didnt specified how to interact with the other smart homes component. The paper designed an interaction model composed of three kinds of service pack and signal-slot mechanism, the model provided a simple way to identify the device status and manage x73 messages. And it did an experiment about R wave detection to verify the interaction model successfully. The paper promotes the application of x73 standard in the interaction between healthcare devices and the other smart homes component.

A new frequency conversion pressure water supply algorithm with efficiency and low-power consumption has been proposed for residents’ district. An inverter was used for start-up, running and frequency conversion to drive three motors in the algorithm, one extra motors together with the other three were running with the recycling mode and timing pump change mode. The data acquisition and device status control were through the inverter and PLC connection, so as to achieve the constant pressure water supply of residential area. On-site commissioning and operation shows the effectiveness of the algorithm.

© 2017 Moss et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Two recent Phase III clinical trials to investigate an intravaginal ring for preventing HIV infection demonstrated that adherence to prescribed device use was a primary driver of efficacy. Surrogate methods for determining adherence in the studies were limited in their inability to monitor temporal patterns of use and allow deconvolution of the effects of adherence and device efficacy on HIV infection rates. To address this issue, we have developed functionality in an intravaginal ring to continuously monitor when the device is being used and maintain a log of adherence that can be accessed by clinicians after it is removed. An electronic module fabricated with common, inexpensive electronic components was encapsulated in a silicone intravaginal ring. The device uses temperature as a surrogate measure of periods of device insertion and removal, and stores a record of the data for subsequent retrieval. The adherence-monitoring intravaginal ring accurately recorded the device status over 33 simulated IN-OUT cycles and more than 1000 measurement cycles in vitro. Following initial in vitro testing in a temperature-controlled chamber, the device was evaluated in vivo in sheep using a predetermined insertion/removal pattern to simulate intravaginal ring use. After insertion into the vaginal cavity of a sheep, the logged data correctly indicated the device status over 29 hours of continuous measurement including three cycles of insertion and removal. The device described here is a promising, low-cost method for real-time adherence assessment in clinical trials involving medicated intravaginal rings or other intravaginal devices.

This paper briefly summarized the logical structure of the model’s attribute characteristics in the wireless sensor network management system of coal enterprise. Due to all kinds of mapping relations between different datum, while extracting some device status information, we can detect it by the method of hierarchical search, and according to the determined geographical location, then obtain the attribute and graphic information, finally get all the relative information of the device, so that the information management system is fast and convenient to be used.

Background With increasing research on system integration for imageguided therapy (IGT), there has been a strong demand for standardized communication among devices and software to share data such as target positions, images and device status.

Well-designed network traffic collection provides a wealth of information regarding what a network-centric system is doing. Analysis tools examine the data and readily help answer what, but why and how may not be attainable, even with advanced analytics. Collecting device status information can augment network traffic information to help answer why and how. To answer these questions, the Aberdeen Test Center developed an active device status collector and collaborated with the US Army Research Laboratory to develop a high-performance-computing solution for correlating device status data with network traffic data.

Failure Mode and Effects Analysis (FMEA) is a well-known design tool used to analyze component failures and identify the resultant effects. Traditional FMEA model requires engineers' input on estimating technical detection difficulty of part failure. Moreover, failure occurrence can only be computed based on historical maintenance data. However, under the IoT based environment, sensors installed on connected devices can transmit continuous signals of device status, which is greatly helpful to make the device failure analytical work more efficient, more objective and more accurate. In this paper, we propose a new FMEA model based on connected device data. A new failure a difficulty creator is proposed to objectively compute detection difficulty. Failure occurrence level is intelligently generated by a new occurrence creator. A house-roof shaped failure correlation creator is designed to mine the correlation of failures. Finally, a new risk RPN estimation method is used to rank the risk of failure.

A new method of diagnosis prediction based on adaptive filtering and HMM is proposed. Firstly, the feature extraction of time-sequence about collected diagnosis information is conducted, achieving time-sequence status information, and then on the basis of the results the future device status information vectors are obtained by means of adaptive filtering. Secondly, the HMMs for all diagnosis statuses are established and be trained according to the algorithm of Baum-Welch, meanwhile HMMs is regarded as the classifier. Lastly, the obtained time-sequence about future status are inputted into HMMs, getting the prediction results in accordance with the criterion of maximum likelihood. The experimental results prove the feasibility for this method, and its prediction accuracy is improved to some extent.

An overview is given of recent laboratory developments in wide-bandgap semiconductor diode lasers. We concentrate on the device science of these blue - green light emitters and outline some of the existing key technical challenges. Following a description of the current device status of the edge-emitting GaN- and ZnSe-based heterojunction lasers, we illustrate the special features of wide-gap semiconductor lasers by focusing on the physics of optical gain and possibilities in short-vertical-cavity structures.

In this paper, we describe a new interactive museum guide system that provides both interactive guidance and map navigation. By using ubiquitous communication such as NFC, the system can automatically start a multimedia guidance with interactive GUI, also support a map view with zoom function to show the visit’s current position and visiting status. The new system also provides a powerful and efficient device management performance that can monitor the device status and update the contents in the devices and obtain the user’s operation data. The new system is used to provide a guide service in several museums in Japan and a good performance was confirmed.

An overview is given of recent developments in wide bandgap semiconductor lasers. Following a description of the current device status of the ZnSe and GaN-based heterojunction emitters, physics of excitons at high densities and optical microcavities are considered; respectively.

As an important basic node of strong smart grid, smart substation is an important part of construction of smart grid. Compared with conventional substation, smart substation adds intelligent terminal, merging unit, electronic instrument transformer, on-line monitoring and other primary intelligent equipment, which increase the construction cost considerably. Moreover, the application of sequential control, device status visualization and other advanced functions reduces the operation cost instead. Therefore, analyzing the life cycle cost and intelligent investment benefit of smart substation timely is of great significance, providing reference and basis for controlling the construction cost level of smart substation and optimizing design scheme. Taking a sample of smart substations in operation, this paper analyzes the difference of life cycle cost between smart substation and conventional substation of the same scale, and calculates the economic benefit of intelligent investment in smart substation. Finally, various measures affecting the life cycle cost of smart substation are quantitatively analyzed by sensitivity analysis.

Currently, off-line defense against the current operating system can not accurately detect the device error status, can not really prevent “walking space” and the construction of complex line against wrong operating system, electromagnetic interference and other drawbacks, the paper offers wireless communication line based on the operating system of error prevention. The system can accurately detect real-time device status, complete “defense away empty”, the construction is simple, no interference. The error system of defense for enhancing the safe operation of substations, reducing the complexity of construction of great significance.

In this paper we propose a gentle system for watching over for pervasive care-support services that fulfill users' actual requirements and without interfering the users' privacy. In this system, we cope with not only the user's physical location but also all the situations of pervasive devices and requirements of associated users, in "both" sides of watching and watched sites. Moreover, social relationships between observers and a watched person are used to give an adequate privacy level to the services. To do this, we propose a pervasive watching over system "uEyes". In uEyes we introduce three distinguished features for the watching, they are (S1) Device awareness, (S2) User awareness and (S3) Social awareness. To realize these features, an autonomous decision making ability and cooperative behavior are employed to each element in the system. Based on these advanced features, a live video streaming system is autonomously constructed according to the device status and the user's situation, on both sides in runtime. As a result, the gentle watching-over service can be effectively provided.

This paper presents an apparatus to facilitate a switch system of the computing device status. The apparatus includes a memory device to store previous and present computer statuses, a requisition device, and switch control device. By achieving and retrieving all the information about alterable status registers, the apparatus can recognize each switch of operating system status. It can also process multi operating systems in a single compute unit. It functions to recognize rapidly and safely status exchanges between internal and external networks.

Publisher Summary This chapter provides an insight into the actuator sensor interface (AS-i). The AS-i is an open system network developed by eleven manufacturers who created the AS-i association to develop the AS-i specifications. Some of the more famous members of the association include Pepperl-Fuchs, Allen-Bradley, Banner Engineering, Datalogic Products, Siemens, Telemecanique, Turck, Omron, Eaton, and Festo. AS-i is a bit-oriented communication link, designed to connect binary sensors and actuators. Most of these devices do not require multiple bytes to adequately convey the necessary information about the device status, so the AS-i communication interface is designed for bit-oriented messages in order to increase message efficiency for these types of devices. AS-i uses a two-wire untwisted, unshielded cable that serves as both communication link and power supply for up to thirty-one slaves. A single master module controls communication over the AS-i network, which can be connected in various configurations such as bus, ring, or tree. The data-link layer of the AS-i network consists of a master call-up and slave response. The master call-up is exactly fourteen bits in length while the slave response is 7 bits.

In order to effectively maintain the operation of the Stanford Linear Collider, the variation over time of control system device parameters and feedback loops must be known. Device status must reflect unwanted variations as well as current states. The software facility which provides the collection and display of history data, and the determination of a behavioral status are discussed. The facility's operation, internal design, and user interface are described. >

Background: Our hospital is situated in rural Japan. Remote monitoring systems for cardiac-implanted devices, such as implantable pacer-generators (IPG) or implantable cardioverter-defibrillators (ICD), are usable in areas hardly accessible by means of public transportation. However, the systems are not readily operable by elderly patients.Objective: Clarification on the feasibility of using the system, and problems on the remote monitoring system.Method: Form April 2010 to May 2011, we introduced remote monitoring systems for 26 patients (mean age: 71.3±10.6; %male 84%). We retrospectively studied the patients, background, the frequency of transmission, and the data transmitted. And we compared the frequency of transmission by the elderly group (age >=75) with the younger group.Results: The implanted devices were ICD for 20 cases (16 cases, with Optivol system) and IPG for 6 cases (3 cases, with ATP system). Frequency of transmission: 95 (total), 3.8±3.2 (mean and SD), 89 (planned), 11 (unplanned), respectively. In the elderly group, the frequency of transmission: 2.1±1.7, which was smaller than in the younger group (4.9±3.5, p

Periodic measurements of urine volume and temperature in critically ill patients are time consuming, unclean procedures. These measurements may be automated with an electronic urimeter (Urotrack Plus 220, C.R. Bard Company, Murray Hill, NJ). This device contains an RS-232 output port which transmits a complete device status report once per second. We interfaced 20 Urotrack Plus urimeters to a single I/O port of a computerized patient data management system (Hewlett-Packard 78709A PDMS, Hewlett-Packard Company, Waltham, MA). This interface required daisy chained controllers for port switching and a communications adapter for flow control. The urimeters have proven to be cost-effective, labor-saving devices. The PDMS interface provides a continuous display of measured variables and completely automates data entry for flowsheet documentation. Automatic urimetry data acquisition is estimated to save approximately 27 nursing minutes per patient per day.