i-manager Publications

i-manager's Journal on Embedded Systems (JES)

Current Issue Vol. 12 Issue 1

Most Cited

Volume 7 Issue 1 July - December 2018

Research Paper

Crosstalk Noise Detection and Monitoring in WDM-Based Optical Network on Chip

Ahmed Jedidi* , Maha Ebrahim Khalifa Al-Sadoon**

*Assistant Professor, Department of Computer and Telecommunication Engineering, College of Engineering, Ahlia University, Bahrain & Member, Computer & Embedded Systems laboratory, University of Sfax, Tunisia.

** Postgraduate in Information Technology & Computer Science, Ahlia University, Bahrain.

Jedidi,A.,and Al Sadoon,M.(2018). Crosstalk Noise Detection and Monitoring in Wdmbased Optical Network on Chip.i-manager's Journal on Embedded Systems,7(1),1-10. https://doi.org/10.26634/jes.7.1.14467

Abstract

Multiprocessor System-on-Chip (MPSoC) is an attractive solution to provide a high performance computing required by the new applications are growing exponentially such as in multimedia applications. However, the communication between processors' cores presents a serious problem in the era of MPSoC. The network on chip (NoC) is presented as a promising solution is acknowledged that it is still limited with increasing data exchange. Moreover, the traditional NoC faces two main problems: the bandwidth and energy consumption. However, a new technology in MPSoC, namely,optical network-on-chip (ONoC) has been introduced which uses optical communication. In addition, wavelength division multiplexing (WDM) is exploited in ONoC to reach a high rate of bandwidth. Nevertheless, the ONoC components inducing crosstalk noise to the optical signal and direct effect the signal-to-noise ratio(SNR). In this article, new system has been proposed to address these impairments in the network in order to detect and monitor crosstalk noise in WDMbased ONoC. The register-transfer level (RTL) hardware design and implementation of this system can result in high reliability, scalability and efficiency with running time less than 20 ms.

References

[1]. Bonetto, E., Chiaraviglio, L., Cuda, D., Castillo, G. A. G., & Neri, F. (2009, September). Optical technologies can improve the energy efficiency of networks. In Optical Communication, 2009. ECOC'09. 35^th European Conference on (pp. 1-4). IEEE.

[2]. Chan, J., Hendry, G., Bergman, K., & Carloni, L. P. (2011). Physical-layer modeling and system-level design of chip-scale photonic interconnection networks. IEEE Transactions on Computer-aided Design of Integrated Circuits and Systems, 30(10), 1507-1520.

[3]. Cianchetti, M. J., Kerekes, J. C., & Albonesi, D. H. (2009). Phastlane: A rapid transit optical routing network. ACM SIGARCH Computer Architecture News, 37(3), 441- 450.

[4]. Ding, W., Tang, D., Liu, Y., Chen, L., & Sun, X. (2010). Compact and low crosstalk waveguide crossing using impedance matched metamaterial. Applied Physics Letters, 96(11), 111-114.

[5]. Dong, P., Qian, W., Liao, S., Liang, H., Kung, C. C., Feng, N. N., ... & Asghari, M. (2010, July). Low loss silicon waveguides for application of optical interconnects. In Photonics Society Summer Topical Meeting Series, 2010 IEEE (pp. 191-192). IEEE.

[6]. Duong, L. H., Nikdast, M., Le Beux, S., Xu, J., Wu, X., Wang, Z., & Yang, P. (2014). A case study of signal-to-noise ratio in ring-based Optical Networks-on-Chip. IEEE Design & Test, 31(5), 55-65.

[7]. Duong, L. H., Wang, Z., Nikdast, M., Xu, J., Yang, P., Wang, Z., ... & Le Beux, S. (2016). Coherent and incoherent crosstalk noise analyses in interchip/intrachip optical interconnection networks. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 24(7), 2475- 2487.

[8]. Fusella, E., & Cilardo, A. (2016). Crosstalk-aware automated mapping for optical networks-on-chip. ACM Transactions on Embedded Computing Systems (TECS), 16(1), 16:1-16:26.

[9]. Gambini, F., Faralli, S., Pintus, P., Andriolli, N., & Cerutti, I. (2015). BER evaluation of a low-crosstalk silicon integrated multi-microring network-on-chip. Optics Express, 23(13), 17169-17178.

[10]. Gu, H., Xu, J., & Zhang, W. (2009, April). A low-power fat tree-based optical network-on-chip for multiprocessor system-on-chip. In Proceedings of the Conference on Design, Automation and Test in Europe (pp. 3-8). European Design and Automation Association.

[11]. Jedidi, A., Rejeb, R., & Abid, M. (2010). Detection and localization of crosstalk in an all-optical network. Journal of Optics, 13(1), 015506.

[12]. Nikdast, M., Xu, J., Duong, L. H. K., Wu, X., Wang, X., Wang, Z., ... & Hao, Q. (2015). Crosstalk noise in WDMbased optical networks-on-chip: A formal study and comparison. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, (11), 2552-2565.

[13]. Nikdast, M., Xu, J., Wu, X., Zhang, W., Ye, Y., Wang, X., ... & Wang, Z. (2014). Systematic analysis of crosstalk noise in folded-torus-based Optical Networks-on-Chip. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 33(3), 437-450.

[14]. Wang, Z., Xu, J., Wu, X., Ye, Y., Zhang, W., Nikdast, M., ... & Wang, Z. (2014). Floorplan optimization of fat-tree-based networks-on-chip for chip multiprocessors. IEEE Transactions on Computers, 63(6), 1446-1459.

[15]. Xie, Y., Nikdast, M., Xu, J., Wu, X., Zhang, W., Ye, Y., ... & Liu, W. (2013). Formal worst-case analysis of crosstalk noise in mesh-based Optical Networks-on-Chip. IEEE Transactions on Very Large Scale Integration (VLSI) Systems, 21(10), 1823-1836.

[16]. Xie, Y., Nikdast, M., Xu, J., Zhang, W., Li, Q., Wu, X., ... & Liu, W. (2010, June). Crosstalk noise and bit error rate analysis for optical network-on-chip. In Design Automation Conference (DAC), 2010 47^th ACM/IEEE (pp. 657-660). IEEE.

[17]. Xie, Y., Xu, J., Zhang, J., Wu, Z., & Xia, G. (2012). Crosstalk Noise Analysis and Optimization in 5 x 5 Hitless Silicon-based Optical Router for Optical Networks-on- Chip (ONoC). Journal of Lightwave Technology, 30(1), 198-203.

[18]. Zhang, L., Regentova, E. E., & Tan, X. (2011, May). A 2D-torus based packet switching Optical Network-on- Chip architecture. In Photonics and Optoelectronics (SOPO), 2011 Symposium on (pp. 1-4). IEEE.

Full Article (HTML)

Pdf

Research Paper

Alcohol Detecting and Notification System for Controlling Drink Driving

Oloyede Mukhtar Abiodun* , Michael David, Waheed Moses Audu*

Undergraduate,Department of Telecommunication Engineering,Federal University of Technology,Minna,Nigeria.

Lecturer, Federal University of Technology, Minna, Nigeria.

Lecturer II, Federal University of Technology, Minna, Nigeria.

Abiodun,O.M., David,M., and Audu,W.M.(2018).Alcohol Detecting and Notification System for Controlling Drink Driving.i-manager's Journal on Embedded Systems,7(1),11-17. https://doi.org/10.26634/jes.7.1.15658

Abstract

It takes being alive and healthy to tackle challenges for sustainable development as well as harness the benefits thereof. The scourge of drink driving has led to loss of life and properties. Control measures to ensure drivers are not under the influence of alcohol while driving such as Blood Alcohol Content (BAC) check remains unrealizable due to the huge personnel, equipment and maintenance cost involved. A less consuming effort has been proposed using mq3 gas sensor mounted on the steering wheel, powered by the ignition of the vehicle, to detect alcohol level of the subject controlling it. The alcohol detected from the subject is processed by an ATMEGA 16 Microcontroller that compares it with a set threshold for compliance. If the threshold is exceeded three modules are simultaneously triggered. The fuel supply control module is activated by a relay to cutoff supply towards bringing the vehicle to a momentary halt. The Liquid Crystal Display (LCD) module is activated to show alcohol has been detected. The Global System for Mobile communication (GSM) module sends the same notice on the LCD to subject's next-of-kin/law- enforcement-agent phone line for immediate attention. This system was developed and tested using a toy car. The result showed that it could be implemented in real life situation provided that all specifications are taken into consideration.

References

[1]. Chambers, M., Liu, M., & Moore, C. (2013). Drunk Driving by Numbers. Bureau of Transportation Statistics. Retrieved from https://www.bts.gov/archive/publications/ by_the_numbers/drunk_driving/index

[2]. Dai, J., Teng, J., Bai, X., Shen, Z., & Xuan, D. (2010, March). Mobile phone based drunk driving detection. In Pervasive Computing Technologies for Healthcare (Pervasive Health), 2010 4^th International Conference on- No Permissions (pp. 1-8). IEEE

[3]. History of Drugs and Alcohol Testing. (n.d). In The Dräger Review. Retrieved from https://www.draeger.com/ Library/Content/history-of-alcohol-testing-en.pdf

[4]. James, N., Aparna, C., & John, T. P. (2014). Alcohol Detection System. International Journal of Research in Computer and Communication Technology Advance Technology, 3(1), 56-64.

[5]. Khan, S., & Khan, S. (2013). High sensitive alcohol sensor with auto car ignition disable function. International Journal of Scientific & Engineering Research, 4(10), 1573-1581.

[6]. Kousikan, M., & Sundaraj, M. (2014). Automatic drunken drive prevention system. International Journal of Students Research in Technology & Management, 2(2), 74-77.

[7]. Navarro, L. A., Dino, M. A., Joson, E., Anacan, R., & Cruz, R. D. (2016). Design of alcohol detection system for car users through iris recognition pattern using wavelet transform. 7^thInternational Conference on Intelligent Systems, Modeling and Simulation (pp. 15-19).

[8]. Vaishnavi, M, Umadevi, V, Vinothini, M, Rao, B. Y., & Pavithra, S. (2014). Intelligent alcohol detection system for car. International Journal of Scientific & Engineering Research, 5(11), 598-601.

Full Article (HTML)

Pdf

Research Paper

An IoT Based Smart Campus Architecture for Institutions in Developing Countries

Barroon Isma’eel Ahmad* , Muhammad Aminu Umar, Mohammed Yahaya Tanko*, M. Pradeep kumar**, Ahmad Aminu Sambo*, Aminu Onimisi Abdulsalami, Abdulrazak Abdulrahim***

Professor,Department of Computer Science,Ahmadu Bello University, Zaria, Nigeria.

_,Lecturer,Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria.

**Assistant Lecturer,Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria.

Ahmad,B.I., Umar,M.A., Tanko,M.Y., Tenuche,S.S., Sambo,A.A., Abdulsalami,A.O., and Abdulrahim,A.(2018). An IoT Based Smart Campus Architecture for Institutions in Developing Countries. i-manager's Journal on Embedded Systems,7(1),18-25. https://doi.org/10.26634/jes.7.1.15635

Abstract

Internet of Things (IoT) related research has become an essential part of the growth of computing, as such there is the need to respond to the challenges of utilizing this aspect. Educational institutions should not be an exception, as they provide enabling environments to study and apply these possibilities. IoT is novel and holds the potentials of driving computing everywhere and anywhere. It also provides the possibility to collect and process variety of data that could widely influence smart campus initiatives. Smart campus makes institutions smarter and safer with improved efficiency and experiences for both students and staff. This paper explored smart campus concept and proposed a framework that could provide value added services for various people within the university environment. The components of the smart campus considered in this paper are smart education, smart mobility, smart health services, smart building and access control management.

References

[1]. Abuarqoub, A., Abusaimeh, H., Hammoudeh, M., Uliyan, D., Abu-Hashem, M. A., Murad, S., ... & Al-Fayez, F. (2017, July). A survey on Internet of Thing enabled smart campus applications. In Proceedings of the International Conference on Future Networks and Distributed Systems (p. 38). ACM.

[2]. Adamkó, A., Kãdek, T., & Kósa, M. (2014, November). Intelligent and adaptive services for a smart campus. In Cognitive Infocommunications (CogInfoCom), 2014 5^th IEEE Conference on (pp. 505-509). IEEE.

[3]. Alghamdi, A., & Shetty, S. (2016, August). Survey toward a smart campus using the internet of things. In Future Internet of Things and Cloud (FiCloud), 2016 IEEE 4^th International Conference on (pp. 235-239). IEEE.

[4]. Bakken, J. P., Uskov, V. L., Penumatsa, A., & Doddapaneni, A. (2016). Smart universities, smart classrooms and students with disabilities. In Smart Education and e-Learning 2016 (pp. 15-27). Springer, Cham.

[5]. Cheng, X., & Xue, R. (2016, May). Construction of smart campus system based on cloud computing. In Proceedings of the 2016 6^th International Conference on Applied Science, Engineering and Technology, Series: Advances in Engineering Research (Vol. 10, pp. 0187- 0191). https://doi.org/ 10.2991/icaset-16.2016.37

[6]. Elsaadany, A., & Soliman, M. (2017). Experimental evaluation of Internet of Things in the educational environment. International Journal of Engineering Pedagogy (IJEP), 7(3), 50-60. https://doi.org/ 10.3991/ijep.v7i3.7187.

[7]. Grizzell, J., & McNeil, M. (2007). Linking health to academic success and retention. Spectrum, 20-24. Retrieved from https://und.edu/health-wellness/healthyund/ linking-health-to-academic-success- retention.pdf

[8]. Halawani, T., & Mohandes, M. (2003, December). Smart card for smart campus: KFUPM case study. In Electronics, Circuits and Systems, 2003. ICECS 2003. Proceedings of the 2003 10^th IEEE International Conference on (Vol. 3, pp. 1252-1255). IEEE.

[9]. Intel. (n.d.). Intel End to End Smart Campus Solution. Success Story: Internet of Things (IoT), Smart Campus. Retrieved from https://www.intel.com/ content/dam/ www/public/us/en/ documents/solution-briefs/end-to- end- smart-campus-solution-brief.pdf

[10]. Kumar, S. T. H., Sriraksha, T. A., & Saba, N. U. (2017). An IoT based secured smart e-Campus. International Journal of Humanities and Social Science Invention, 6(3), 88-93.

[11]. Phougat, K., Sinha ,M., Pruthi, S., Wakurdekar, S. B. (2017). An IoT approach for developing a smart campus. International Journal of Innovative Research in Computer and Communication Engineering, 5(4), pp. 7405-7412.

[12]. Sari, M. W., Ciptadi, P. W., & Hardyanto, R. H. (2017, April). Study of smart campus development using Internet of Things technology. In IOP Conference Series: Materials Science and Engineering (Vol. 190, No. 1, p. 012032). IOP Publishing.

[13]. Stavropoulos, T. G., Tsioliaridou, A., Koutitas, G., Vrakas, D., & Vlahavas, I. (2010, September). System architecture for a smart university building. In International Conference on Artificial Neural Networks (pp. 477-482). Springer, Berlin, Heidelberg.

[14]. Sultan, M. N., Ali, E., Ali, M., Nadim, M., & Habib, A. M. (2017). Smart campus using IoT with Bangladesh Perspective: A possibility and limitation. International Journal for Research in Applied Science & Engineering Technology (IJRASET), 5(8), 1681-1690.

[15]. Veeramanickam, M. R. M., & Mohanapriya, M. (2017). IoT enabled futurus smart campus with effective ELearning: i-Campus. GSTF Journal of Engineering Technology (JET), 3(4), 81-87.

[16]. Verstaevel, N., Boes, J., & Gleizes, M. P. (2017). From smart campus to smart cities: issues of the smart revolution. IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computed, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 1-6).

[17]. Wang, H. (2013). Toward a Green Campus with the Internet of Things-the Application of Lab Management. Proceedings of the World Congress on Engineering (Vol. 2).

Full Article (HTML)

Pdf

Research Paper

Wireless Sensor Irrigation System for Monitoring Different Parameters

S. G. Galande* , C. S. Galande**

*Associate Professor, Department of E&TC Engineering, PREC, Loni, Ahmednagar, India.

**Assistant Professor,Department of BCS, PVP College, Loni, Ahmednagar, India.

Galande,S.G., and Galande,C.S.(2018).Wireless Sensor Irrigation System for Monitoring Different Parameters. i-manager's Journal on Embedded Systems,7(1),26-29. https://doi.org/10.26634/jes.7.1.15310

Abstract

Water management in agriculture is a major concern in agriculture based country. There is a need to develop conservation mechanisms to make better use of water as well as to increase crop productivity. This can be done by the development of automated irrigation system that takes into account several factors, such as soil moisture, temperature, etc. One of the more popular methods is drip irrigation system. Drip irrigation supplies water drop by drop to root zone of plants through pipes containing several emitters. This irrigation system is composed of the following components: water source which is connected with a main tube called main pipeline. To this line, several pipes are connected using manual or electrical valves that control the water flow. The proposed system is used for sensing, monitoring, controlling, and communication purpose. Sensors are used for detecting different parameters such as moisture for checking the contents of water in the soil and temperature used for checking evaporation rate of water. Output of this sensor is provided to the ARM7 processor. ARM7 processor has lower and upper set point values and according to this set point provided by the ARM7 processor actions such as ON or OFF of the water control valve will happen. Advantages of the system are improved estimation and planning of field irrigation based on the available water supply. The system will optimize the required human resources, time, and effort in the agricultural production.

References

[1]. Dubey, V., Dubey, N., & Chouhan, S. S. (2011, June). Wireless sensor network based remote irrigation control system and automation using DTMF code. In Communication Systems and Network Technologies (CSNT), 2011 International Conference on (pp. 34-37). IEEE.

[2]. Galgalikar, M. M. (2010, February). Real-time automization of agricultural environment for social modernization of Indian agricultural system. In Computer and Automation Engineering (ICCAE), 2010 The 2^nd International Conference on (Vol. 1, pp. 286-288). IEEE.

[3]. Gutiérrez, J., Villa-Medina, J. F., Nieto-Garibay, A., & Porta-Gándara, M. Á. (2014). Automated irrigation system using a Wireless Sensor Network and GPRS module. IEEE Transactions on Instrumentation and Measurement, 63(1), 166-176.

[4]. Kim, Y., Evans, R. G., & Iversen, W. M. (2008). Remote sensing and control of an irrigation system using a distributed Wireless Sensor Network. IEEE Transactions on Instrumentation and Measurement, 57(7), 1379-1387.

[5]. Kumbhar, S. R., & Ghatule, A. P. (2013, March). Microcontroller based controlled irrigation system for plantation. In Proceedings of the International Multi Conference of Engineers and Computer Scientists (Vol. 2).

[6]. Mafuta, M., Zennaro, M., Bagula, A., Ault, G., & Chadza, T. (2013). Successful deployment of a Wireless Sensor Network for precision agriculture in Malawi–WiPAM. In 3^rd IEEE International Conference on Networked Embedded Systems for every Application.

[7]. Nemali, K. S., & van Iersel, M. W. (2006). An automated system for controlling drought stress and irrigation in potted plants. Scientia Horticulturae, 110(3), 292-297.

[8]. Nikolidakis, S. A., Kandris, D., Vergados, D. D., & Douligeris, C. (2015). Energy efficient automated control of irrigation in agriculture by using wireless sensor networks. Computers and Electronics in Agriculture, 113, 154-163.

[9]. O'Shaughnessy, S. A., & Evett, S. R. (2010). Canopy temperature based system effectively schedules and controls center pivot irrigation of cotton. Agricultural Water Management, 97(9), 1310-1316.

[10]. Sudha, M. N., Valarmathi, M. L., & Babu, A. S. (2011). Energy efficient data transmission in automatic irrigation system using Wireless Sensor Networks. Computers and Electronics in Agriculture, 78(2), 215-221.

Full Article (HTML)

Pdf

Research Paper

Simulation of Real Time Multiprocessor Static Scheduling Algorithms

Madhu Kumar Patnala* , R. Nagendra**

*_**Assistant Professor (SL), Center for VLSI & Embedded Systems, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, India.

Patnala,M.K.,and Nagendra,R.(2018). Simulation of Real Time Multiprocessor Static Scheduling Algorithms. i-manager's Journal on Embedded Systems,7(1),30-36. https://doi.org/10.26634/jes.7.1.15134

Abstract

Real Time Systems are time bound systems. Their efficiency is dependent on logical correctness as well as strict timeframe within which they react to an event. Completion within deadline is stressed especially in hard real time systems. Modern embedded hardware implementations choose multiprocessor architectures to support multitasking. Multiprocessor scheduling problem can be broken down in terms of task to processor assignment prior to uniprocessor scheduling problem. Suitable task to processor allocation strategy to uniprocessor scheduling algorithms like RMA and EDF for developing multiprocessor scheduler can be combined. This paper demonstrates simulation of Utilization Balancing algorithm for EDF, Next-fit algorithm for RMA, Bin packing algorithms for EDF using C language and TORSCHE tool box for MATLAB. The Objective of this work is to analyze various static scheduling algorithms for usage in multiprocessor based embedded systems.

References

[1]. Anderson, J. H., & Srinivasan, A. (2000). Early-release fair scheduling. In Real-Time Systems, 2000. Euromicro RTS 2000. 12^thEuromicro Conference on (pp. 35-43). IEEE.

[2]. Andersson, B., & Jonsson, J. (2003, July). The utilization bounds of partitioned and pair static-priority scheduling on multiprocessors are 50%. In Real-Time Systems, 2003. Proceedings. 15^th Euromicro Conference on (pp. 33-40). IEEE.

[3]. Carpenter, J., Funk, S., Holman, P., Srinivasan, A., Anderson, J. H., & Baruah, S. K. (2004). A categorization of real-time multiprocessor scheduling problems and algorithms. In Handbook of Scheduling Algorithms, Methods, and Models. Chapman Hall/CRC, Boca.

[4]. Funk, S., Goossens, J., & Baruah, S. (2001, December). On-line scheduling on uniform multiprocessors. In RTSS (p. 183-192). IEEE.

[5]. Goossens, J., & Richard, P. (2004, April). Overview of real-time scheduling problems. In Euro Workshop on Project Management and Scheduling.

[6]. Hemanth, R., & Kumar, P. M. (2014). Real time usercentric energy efficient scheduling in embedded systems. i-manager's Journal on Embedded Systems, 3(3), 31-38.

[7]. Leung, J. Y. (Ed.). (2004). Handbook of Scheduling: Algorithms, Models, and Performance Analysis. CRC Press, Boca Raton, FL, USA.

[8]. Mall, R. (2009). Real-time Systems: Theory and Practice. Pearson Education India.

[9]. Perkins, C. (2005). Course Notes: Overview of Real- Time Scheduling, Real-Time and Embedded Systems (M) Lecture 3. University of Glasgow, Department of Computing Science Academic Year 2004-2005.

Full Article (HTML)

Pdf

Research Paper

IoT Based Single-Phase Energy Meter and Monitoring System

Anilkumar V. Nandi* , Vaishali B. Mungurwadi, B. Jean*

Professor, Department of Electronics and Communication Engineering, KLE Technological University, Karnataka, India.

Principal, Sarvajanik College of Engineering & Technology, Surat, Gujarat,India.

Undergraduate, Department of Electronics and Communication Engineering, B.V. Bhoomaraddi College of Engineering & Technology,Karnataka,India.

Nandi,A.V., Mungurwadi,V.B.and Mannur,P.P.(2018).IoT Based Single-Phase Energy Meter and Monitoring System.i-manager's Journal on Embedded Systems,7(1),37-44. https://doi.org/10.26634/jes.7.1.14568

Abstract

The Internet of things allows object to be sensed and actuated remotely across existing network infrastructure, creating opportunities for more direct integration between the physical world and computer-based systems, and resulting in improved efficiency, accuracy and economic benefit. In this applied research, a real time energy monitoring system employing IOT is proposed. This is a cost-effective system consisting of a energy meter and a user-friendly android app, which can be installed in a local residence for energy monitoring and the data can be uploaded to cloud through which detailedinformation and pattern of energy consumption of the house can be accessed remotely or locally by the user. Through this system there will be reduction in the wastage of energy and can be used as a platform for efficient energy management.

References

[1]. Arampatzis, T., Lygeros, J., & Manesis, S. (2005, June). A survey of applications of wireless sensors and wireless sensor networks. In Intelligent Control, 2005. Proceedings of the 2005 IEEE International Symposium on, Mediterrean Conference on Control and Automation (pp. 719-724). IEEE.

[2]. Ashraf, Q. M., Yusoff, M. I. M., Azman, A. A., Nor, N. M., Fuzi, N. A. A., Saharedan, M. S., & Omar, N. A. (2015, December). Energy monitoring prototype for Internet of Things: Preliminary results. In Internet of Things (WF-IoT), 2015 IEEE 2^nd World Forum on (pp. 1-5). IEEE.

[3]. Chen, X. Y., & Jin, Z. G. (2012). Research on key technology and applications for Internet of Things. Physics Procedia, 33, 561-566.

[4]. Chorost, M. (2008). The networked pill. EmTech Technology Review.

[5]. ESP-32SoC. (2018). Retrieved from https://www.espressif.com/en/products/hardware/esp32/ overview

[6]. ESP8266SoC. (2016). Retrieved from https://github.com/esp8266/Arduino

[7]. Hlaing, W., Thepphaeng, S., Nontaboot, V., Tangsunantham, N., Sangsuwan, T., & Pira, C. (2017, March). Implementation of WiFi-based single phase smart meter for Internet of Things (IoT). In Electrical Engineering Congress (iEECON), 2017 International (pp. 1-4). IEEE.

[8]. Introduction to ThingSpeak. (n.d.). Retrieved from https://www.mathworks.com/videos/introduction-tothingspeak- 107749.html

[9]. Luan, H., & Leng, J. (2016, May). Design of energy monitoring system based on IoT. In Control and Decision Conference (CCDC), 2016 Chinese (pp. 6785-6788). IEEE.

[10]. Nunberg, G. (2012). The Advent of the Internet: 12^th April, Courses.

[11]. Ramakrishnan, R., & Gaur, L. (2016, January). Smart electricity distribution in residential areas: Internet of Things (IoT) based advanced metering infrastructure and cloud analytics. In Internet of Things and Applications (IOTA), International Conference on (pp. 46-51). IEEE.

[12]. Sun, C. (2012). Application of RFID technology for logistics on internet of things. AASRI Procedia, 1, 106-111.

Full Article (HTML)

Pdf

Research Paper

Analysis and Detection of Parametric Fault Detection for Analog Circuit Systems

R. Gurunadha* , K. Babulu**

*Assistant Professor, Department of Electronics and Communication Engineering, JNTUK-UCEV, Vizianagaram, Andhra Pradesh, India.

**Professor, Department of Electronics and Communication Engineering, JNTUK-UCEK, Kakinada, Andhra Pradesh, India.

Gurunadha,R., and Babulu,K.(2018) Analysis and Detection of Parametric Fault Detection for Analog Circuit Systems. i-manager's Journal on Embedded Systems,7(1),45-50. https://doi.org/10.26634/jes.7.1.14634

Abstract

A way to deal with simple fault analysis for circuits with resistance is exhibited dependent on measured fault identification calculation. The proposed model comprises of primer conclusion and choice principles in light of pre-decided values of the threshold. The analysis is performed on the circuit under test, and the relating reactions are acquired from various test focuses (components). The primery determination of result is obtained by utilizing an evidential calculation and fault area which is achieved dependent on the choice of control rules. The test result demonstrates that the proposed conclusion approach can deliver a more significant and precise determination and has the capacity to analyze disastrous and parametric faults in simple circuits with good and perfect precision.

References

[1]. Alippi, C., Catelani, M., Fort, A., & Mugnaini, M. (2002). SBT soft fault diagnosis in analog electronic circuits: A sensitivity-based approach by randomized algorithms. IEEE Transactions on Instrumentation and Measurement, 51(5), 1116-1125.

[2]. Augusto, J. S., & Almeida, C. (2006). A tool for test point selection and single fault diagnosis in linear analog circuits. In Proc. XXI Intl. Conf. on Design of Systems and Integrated Systems DCIS (Vol. 6).

[3]. Cui, J., & Wang, Y. (2011). A novel approach of analog circuit fault diagnosis using support vector machines classifier. Measurement, 44(1), 281-289.

[4]. Czaja, Z., & Zielonko, R. (2004). On fault diagnosis of analogue electronic circuits based on transformations in multi-dimensional spaces. Measurement, 35(3), 293- 301.

[5]. Golonek, T., & Rutkowski, J. (2007). Genetic-algorithm -based method for optimal analog test points selection. IEEE Transactions on Circuits and Systems II: Express Briefs, 54(2), 117-121.

[6]. Luo, H., Wang, Y., & Cui, J. (2011). A SVDD approach of fuzzy classification for analog circuit fault diagnosis with FWT as preprocessor. Expert Systems with Applications, 38(8), 10554-10561.

[7]. Mahdavi, S. S., & Mohammadi, K. (2009). Evolutionary derivation of optimal test sets for neural network based analog and mixed signal circuits fault diagnosis approach. Microelectronics Reliability, 49(2), 199-208.

[8]. Prasad, V. C., & Babu, N. S. C. (2000). Selection of test nodes for analog fault diagnosis in dictionary approach. IEEE Transactions on Instrument and Measurement, 49(6), 1289-1297.

[9]. Prasad, V. C., & Pinjala, S. R. (1995). Fast algorithms for selection of test nodes of an analog circuit using a generalized fault dictionary approach. Circuits, Systems and Signal Processing, 14(6), 707-724.

[10]. Starzyk, J. A., Liu, D., Liu, Z. H., Nelson, D. E., & Rutkowski, J. O. (2004). Entropy-based optimum test points selection for analog fault dictionary techniques. IEEE Transactions on Instrumentation and Measurement, 53(3), 754-761.

[11]. Tao, L., & Dexin, Z. (2010, May). The study of analog circuit fault diagnosis method based on circuit transform function. In Control and Decision Conference (CCDC), 2010 Chinese (pp. 1705-1708). IEEE.

[12]. Wang, P., & Yang, S. (2005). A new diagnosis approach for handling tolerance in analog and mixed- signal circuits by using fuzzy math. IEEE Transactions on Circuits and Systems I: Regular Papers, 52(10), 2118- 2127.

[13]. Yi-Chuang, S. U. N. (2008). Test and Diagnosis of Analogue, Mixed-signal and RF Integrated Circuits (Doctoral Dissertation, London, UK: Institution of Engineering and Technology).

i-manager's Journal on Embedded Systems (JES)

Current Issue Vol. 12 Issue 1

Most Read

Most Cited

Volume 7 Issue 1 July - December 2018

Crosstalk Noise Detection and Monitoring in WDM-Based Optical Network on Chip

Ahmed Jedidi* , Maha Ebrahim Khalifa Al-Sadoon**

*Assistant Professor, Department of Computer and Telecommunication Engineering, College of Engineering, Ahlia University, Bahrain & Member, Computer & Embedded Systems laboratory, University of Sfax, Tunisia. ** Postgraduate in Information Technology & Computer Science, Ahlia University, Bahrain.

Jedidi,A.,and Al Sadoon,M.(2018). Crosstalk Noise Detection and Monitoring in Wdmbased Optical Network on Chip.i-manager's Journal on Embedded Systems,7(1),1-10. https://doi.org/10.26634/jes.7.1.14467

Abstract

References

Full Article (HTML)

Pdf

Alcohol Detecting and Notification System for Controlling Drink Driving

Oloyede Mukhtar Abiodun* , Michael David**, Waheed Moses Audu***

*Undergraduate,Department of Telecommunication Engineering,Federal University of Technology,Minna,Nigeria. **Lecturer, Federal University of Technology, Minna, Nigeria. ***Lecturer II, Federal University of Technology, Minna, Nigeria.

Abiodun,O.M., David,M., and Audu,W.M.(2018).Alcohol Detecting and Notification System for Controlling Drink Driving.i-manager's Journal on Embedded Systems,7(1),11-17. https://doi.org/10.26634/jes.7.1.15658

Abstract

References

Full Article (HTML)

Pdf

An IoT Based Smart Campus Architecture for Institutions in Developing Countries

Barroon Isma’eel Ahmad* , Muhammad Aminu Umar**, Mohammed Yahaya Tanko***, M. Pradeep kumar****, Ahmad Aminu Sambo*****, Aminu Onimisi Abdulsalami******, Abdulrazak Abdulrahim*******

*Professor,Department of Computer Science,Ahmadu Bello University, Zaria, Nigeria. **_****,*******Lecturer,Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria. ******Assistant Lecturer,Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria.

Ahmad,B.I., Umar,M.A., Tanko,M.Y., Tenuche,S.S., Sambo,A.A., Abdulsalami,A.O., and Abdulrahim,A.(2018). An IoT Based Smart Campus Architecture for Institutions in Developing Countries. i-manager's Journal on Embedded Systems,7(1),18-25. https://doi.org/10.26634/jes.7.1.15635

Abstract

References

Full Article (HTML)

Pdf

Wireless Sensor Irrigation System for Monitoring Different Parameters

S. G. Galande* , C. S. Galande**

*Associate Professor, Department of E&TC Engineering, PREC, Loni, Ahmednagar, India. **Assistant Professor,Department of BCS, PVP College, Loni, Ahmednagar, India.

Galande,S.G., and Galande,C.S.(2018).Wireless Sensor Irrigation System for Monitoring Different Parameters. i-manager's Journal on Embedded Systems,7(1),26-29. https://doi.org/10.26634/jes.7.1.15310

Abstract

References

Full Article (HTML)

Pdf

Simulation of Real Time Multiprocessor Static Scheduling Algorithms

Madhu Kumar Patnala* , R. Nagendra**

*_**Assistant Professor (SL), Center for VLSI & Embedded Systems, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, India.

Patnala,M.K.,and Nagendra,R.(2018). Simulation of Real Time Multiprocessor Static Scheduling Algorithms. i-manager's Journal on Embedded Systems,7(1),30-36. https://doi.org/10.26634/jes.7.1.15134

Abstract

References

Full Article (HTML)

Pdf

IoT Based Single-Phase Energy Meter and Monitoring System

Anilkumar V. Nandi* , Vaishali B. Mungurwadi**, B. Jean***

Nandi,A.V., Mungurwadi,V.B.and Mannur,P.P.(2018).IoT Based Single-Phase Energy Meter and Monitoring System.i-manager's Journal on Embedded Systems,7(1),37-44. https://doi.org/10.26634/jes.7.1.14568

Abstract

References

Full Article (HTML)

Pdf

Analysis and Detection of Parametric Fault Detection for Analog Circuit Systems

R. Gurunadha* , K. Babulu**

*Assistant Professor, Department of Electronics and Communication Engineering, JNTUK-UCEV, Vizianagaram, Andhra Pradesh, India. **Professor, Department of Electronics and Communication Engineering, JNTUK-UCEK, Kakinada, Andhra Pradesh, India.

Gurunadha,R., and Babulu,K.(2018) Analysis and Detection of Parametric Fault Detection for Analog Circuit Systems. i-manager's Journal on Embedded Systems,7(1),45-50. https://doi.org/10.26634/jes.7.1.14634

Abstract

References

Full Article (HTML)

Pdf

*Assistant Professor, Department of Computer and Telecommunication Engineering, College of Engineering, Ahlia University, Bahrain & Member, Computer & Embedded Systems laboratory, University of Sfax, Tunisia.

** Postgraduate in Information Technology & Computer Science, Ahlia University, Bahrain.

Oloyede Mukhtar Abiodun* , Michael David, Waheed Moses Audu*

Undergraduate,Department of Telecommunication Engineering,Federal University of Technology,Minna,Nigeria.

Lecturer, Federal University of Technology, Minna, Nigeria.

Lecturer II, Federal University of Technology, Minna, Nigeria.

Barroon Isma’eel Ahmad* , Muhammad Aminu Umar, Mohammed Yahaya Tanko*, M. Pradeep kumar**, Ahmad Aminu Sambo*, Aminu Onimisi Abdulsalami, Abdulrazak Abdulrahim***

Professor,Department of Computer Science,Ahmadu Bello University, Zaria, Nigeria.

_,Lecturer,Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria.

**Assistant Lecturer,Department of Computer Science, Ahmadu Bello University, Zaria, Nigeria.

*Associate Professor, Department of E&TC Engineering, PREC, Loni, Ahmednagar, India.

**Assistant Professor,Department of BCS, PVP College, Loni, Ahmednagar, India.

Anilkumar V. Nandi* , Vaishali B. Mungurwadi, B. Jean*

*Assistant Professor, Department of Electronics and Communication Engineering, JNTUK-UCEV, Vizianagaram, Andhra Pradesh, India.

**Professor, Department of Electronics and Communication Engineering, JNTUK-UCEK, Kakinada, Andhra Pradesh, India.