Sabriansyah Rizqika Akbar

UDP Pervasive Protocol Integration with IoT for Smart Home Environment using LabVIEW

Zigbee technology has been developed for short range wireless sensor networks and it follows IEEE 802.15.4 standard. For such sensors, several considerations should be taken including; low data rate and less design complexity in order to achieve efficient performance considering to the transceiver systems. This research focuses on implementing a digital transceiver system for Zigbee sensor based on IEEE 802.15.4 . The system is implemented using offset quadrature phase shift keying (OQPSK) modulation technique with half sine pulse-shaping method. Direct conversion scheme has been used in the design of Zigbee receiver in order to fulfill the requirements mentioned above. System performance is analyzed considering to BER when it encountered adaptive white Gaussian noise (AWGN), besides showing the effect of using direct sequence spread spectrum (DSSS) technique.The inverted pendulum is an under-actuated and nonlinear system, which is also unstable. It is a single-input double-output system, where only one output is directly actuated. This paper investigates a single intelligent control system using an adaptive neuro-fuzzy inference system (ANFIS) to stabilize the inverted pendulum system while tracking the desired position. The non-linear inverted pendulum system was modelled and built using MATLAB Simulink. An adaptive neuro-fuzzy logic controller was implemented and its performance was compared with a Sugeno-fuzzy inference system in both simulation and real experiment. The ANFIS controller could reach its desired new destination in 1.5 s and could stabilize the entire system in 2.2 s in the simulation, while in the experiment it took 1.7 s to reach stability. Results from the simulation and experiment showed that ANFIS had better performance compared to the Sugeno-fuzzy controller as it provided faster and smoother response and much less steady-state error.Association Rule mining plays an important role in the discovery of knowledge and information. Association Rule mining discovers huge number of rules for any dataset for different support and confidence values, among this many of them are redundant, especially in the case of multi-level datasets. Mining non-redundant Association Rules in multi-level dataset is a big concern in field of Data mining. In this paper, we present a definition for redundancy and a concise representation called Reliable Exact basis for representing non-redundant Association Rules from multi-level datasets. The given non-redundant Association Rules are loss less representation for any datasets.This paper presents a novel technique for numeral reading in Indian language speech synthesis systems using the rule-based Concatenative speech synthesis technique. The model uses a set of rules to determine the context of the numeral pronunciation and is being integrated with the waveform concatenation technique to produce speech out of the input text in Indian languages. To analyze the performance of the proposed technique, a set of numerals are considered in different context and a comparison of the proposed technique with an existing numeral reading method is also presented to show the effectiveness of the proposed technique in producing intelligible speech out of the entered text.This paper presents a data processing system based on an architecture comprised of multiple stacked layers of computational processes that transforms Raw Binary Pollution Data com- ing directly from Two EUMETSAT Metop satellites to our servers, into ready to interpret and visualise continuous data stream in near real time using techniques varying from task automation, data preprocessing and data analysis to machine learning using feed forward ar- tificial neural networks. The proposed system handles the acquisition, cleaning, processing, normalizing, and predicting of Pollution Data in our area of interest of Morocco.Advanced Communication Systems are wideband systems to support multiple applications such as audio, video and data so and so forth. These systems require high spectral efficiency and data rates. In addition, they should provide multipath fading and inter-symbol interference (ISI) free transmission. Multiple input multiple output orthogonal frequency division multiplexing (MIMO OFDM) meets these requirements Hence, MIMO-OFDM is the most preferable technique for long term evaluation advanced (LTE-A). The primary objective of this paper is to control bit error rate (BER) by proper channel coding, pilot carriers, adaptive filter channel estimation schemes and space time coding (STC). A combination of any of these schemes results in better BER performance over individual schemes. System performance is analyzed for various digital modulation schemes. In this paper,adaptive filter channel estimated MIMO OFDM system is proposed by integrating channel coding, adaptivefilter channel estimation, digital modulation and space time coding. From the simulation results, channel estimated 2×2 MIMO OFDM system shows superior performance over individual schemes.Electricity markets are different from other markets as electricity generation cannot be easily stored in large amounts and in order to avoid blackouts, the generation of electricity must be balanced with customer demand for it on a second-by-second basis. Customers tend to rely on electricity for day-to-day living and cannot replace it easily so when electricity prices increase, customer demand generally does not reduce significantly in the short-term. As electricity generation and customer demand must be matched perfectly second-by-second, and because generation cannot be stored to a large extent, cost bids from generators must be balanced with demand estimates in advance of real-time. This paper outlines a a forecasting algorithm built on artificial neural networks in order to predict short-term (72 hours ahead) wholesale prices on the Irish Single Electricity Market so that market participants can make more informed trading decisions. Research studies have demonstrated that an adaptive or self-adaptive approach to forecasting would appear more suited to the task of predicting energy demands in territory such as Ireland. Implementing an in-house self-adaptive model should yield good results in the dynamic uncertain Irish energy market. We have identified the features that such a model demands and outline it here.Received May 2, 2018 Revised Jul 9, 2018 Accepted Aug 2, 2018 Zigbee technology has been developed for short range wireless sensor networks and it follows IEEE 802.15.4 standard. For such sensors, several considerations should be taken including; low data rate and less design complexity in order to achieve efficient performance considering to the transceiver systems. This research focuses on implementing a digital transceiver system for Zigbee sensor based on IEEE 802.15.4. The system is implemented using offset quadrature phase shift keying (OQPSK) modulation technique with half sine pulse-shaping method. Direct conversion scheme has been used in the design of Zigbee receiver in order to fulfill the requirements mentioned above. System performance is analyzed considering to BER when it encountered adaptive white Gaussian noise (AWGN), besides showing the effect of using direct sequence spread spectrum (DSSS) technique. Keyword:This paper presents the use of Simelectronics Program for modeling and control of a two degrees-of freedom coupled mass-spring-damper mechanical system.The aims of this paper are to establish a mathematical model that represents the dynamic behaviour of a coupled mass-spring damper system and effectively control the mass position using both Simulink and Simelectronics.The mathematical model is derived based on the augmented Lagrange equation and to simulate the dynamic accurately a PD controller is implemented to compensate for the oscillation sustained by the system as a result of the complex conjugate pair poles near to the imaginary axis.The input force has been subjected to an obstacle to mimic actual challenges and to validate the mathematical model a Simulink and Simelectronics models were developed, consequently, the results of the models were compared. According to the result analysis, the controller tracked the position errors and stabilized the positions to zero within a settling time of 6.5sec and significantly reduced the overshoot by 99.5% and 99. 7% in Simulink and Simelectronics respectively. Furthermore, it is found that Simelectronics model proved to be capable having advantages of simplicity, less time-intense and requires no mathematical model over the Simulink approach.

Pervasive Device and Service Discovery Protocol in Interoperability XBee-IP Network

The Internet of Things (IoT) communication protocol built over IP and non-IP environment. Therefore, a gateway device will be needed to bridge the IP and non-IP network transparently since an IoT user is more likely to concern on the service provided by the IoT device, rather than the complexity of the network or device configuration. Since today ubiquitous computing needs to hide the architectural level from it users, the data & information centric approach was proposed. However, the data & information centric protocol is having several issues and one of them is device and service discovery protocol over IP & non-IP network. This paper proposed a pervasive device and service discovery protocol that able to work in interoperability of the IP and non-IP network. The system environment consists of a smart device with XBee Communication as the non-IP network that will send the device and service description data to the IP network using WebSocket. The gateway will able to recognize the smart device and sent the data to the web-based user application. The user application displayed the discovered devices along the services and able to send the control data to each of the smart devices. Our proposed protocol also enriched with the smart device inoperability detection by using keep-alive tracking from the gateway to each of the smart devices. The result showed that the delay for the user application to detect the smart device in the XBee network is around 10.13 ms delay, and the service average delay requested by the user application to each of the devices is 2.13 ms.

Lightweight UDP Pervasive Protocol in Smart Home Environment Based on Labview

TCP (Transmission Control Protocol) technology in a reliable environment was not a problem, but not in an environment where the entire Smart Home network connected locally. Currently employing pervasive protocols using TCP technology, when data transmission is sent, it would be slower because they have to perform handshaking process in advance and could not broadcast the data. On smart home environment, it does not need large size and complex data transmission between monitoring site and monitoring center required in Smart home strain monitoring system. UDP (User Datagram Protocol) technology is quick and simple on data transmission process. UDP can broadcast messages because the UDP did not require handshaking and with more efficient memory usage. LabVIEW is a programming language software for processing and visualization of data in the field of data acquisition. This paper proposes to examine Pervasive UDP protocol implementations in smart home environment based on LabVIEW. UDP coded in LabVIEW and experiments were performed on a PC and can work properly.

Pervasive device and service discovery protocol in XBee sensor network

Internet of Things is a novel paradigm that combined microcomputer and wireless communication technology. IoT device will be considered as a pervasive and ubiquitous device that able to interact with it user and environment autonomously with minimum human intervention. At present, wireless technology already has pervasive features in the link and the network layer. They able to do the dynamic addressing, finding a neighbor and do the routing task such as in Xbee technology. In the future, pervasive sensing will support adaptive context-aware services that are not provided by the wireless sensor network protocol in the link and the network layer. Our research proposed pervasive device and service discovery protocol at the application level by creating a protocol in the smart sensor device and the smart sensor gateway. By implementing our protocol, the sensor network gateway is able to find each of the sensor network device and service descriptions and request the on-demand service to the smart sensor device. The protocol is implemented in two Arduino Uno integrated with XBee transceiver as the smart sensor device and the raspberry pi as the smart sensor gateway. Result shows, the gateway was able to find both device and service description in the smart sensor network with 4.13 seconds average time. The average round trip time for request and response data from the gateway is 0.201 seconds.

Using Strongly Typed Genetic Programming for knowledge discovery of course quality from e-learning's web log

Learning Management System (LMS) has become the popular instrument in academic institutions by providing feasible pedagogical interaction. In the abundance of registered users take some activities inside LMS, the result of analyzing the quality of courses becomes remarkable feedback for teachers to enhance their teaching program via e-learning. Unexceptionally, mining web server log has been fascinating area in e-education environment. Our objective is to find interrelationships knowledge among e-learning web logs metrics. Strongly Typed Genetic Programming (STGP) as the cutting the edge technique for finding accurate rule inductions is used to achieve the goal. Revealed knowledge may useful for teachers or academicians to rearrange strategies in the purpose of improving e-learning usage quality based on the course activities.