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nThe reserve of conventional energy sources such as coal, natural gas, and crude oil are rapidly decreasing with increasing demand of electricity in the world. Also, the fossil fuels cause air pollution, global warming, and similar environmental problems. Therefore, recent studies have become widespread about renewable energy sources (RESs) such as biomass, hydropower, geothermal, wind and solar which are the most popular worldwide. Among other RESs, solar energy is assumed as the best alternative to conventional sources of energy. In this study, a micro-inverter (MI) is designed by using isolated boost converter on dc-dc side and full bridge inverter for dc-ac conversion. The power capacity of designed MI is rated at 10kW where the input voltage is 55 V while output voltage is converted to 230 Vrms at 50 Hz frequency. The boost converter is controlled by an INC MPPT controller. The PI controller and fuzzy logic controller are used to control the bridge inverter and the result of both the control methods have been compared.n

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1. Kabalci E, Boyar A, Kabalci Y. Design and analysis of a MI for PV plants. Comput Artif Intell (ECAI), Targoviste, Romania 9th International Conference on Electronics. Vol. 2017; 2017. p. 1–6. doi: 10.1109/ECAI.2017.8166459.
2. KABALCI E, BOYAR A. Design and analysis of a single phase flyback MI 6th International Conference on Control Engineering & Information Technology (CEIT), Istanbul, Turkey, 2018;2018. p. 1–6. doi: 10.1109/CEIT.2018.8751843.
3. Mahela OP, Shaik AG. Comprehensive overview of grid interfaced solar photovoltaic systems. Ren. Rew. 2017;68(February):316–32. doi: 10.1016/j.rser.2016.09.096.
4. Bagher AM, Vahid MMA, Mohsen M. Types of solar cells and application. Am J Opt Photonics. August 21 2015:94–113.
5. Dhivya R, Jaiganesh K, Duraiswamy Dr. K. MATLAB simulation of photovoltaic MI system using MPPT algorithm. Int J Sci Res vol. 4. December 2013:2077–82.
6. Diaz-Bernabe JL, Morales-Acevedo A. Simulation of a double-stage micro-inverter for gridconnected photovoltaic modules, in 2016. Electrical engineering. Mexico: Com (Coca-Cola enterprises inc), September 26–30 2016.
7. Panel SP PV; 14.05.2017. Available from: http://www.solar-facts-andadvice.com/supportfiles/sp_315ewh_en_ltr_p_ds.pdf.
8. Prabaharan N, Palanisamy K. ’Analysis and integration of multilevel inverter configuration with boost converters in a photovoltaic system’, en Con Man vol. 2016;128(15):327–42.
9. Forouzesh M, Siwakoti YP, Gorji SA, Blaabjerg F, Lehman B. Step-up DC–DC converters: A comprehensive review of voltage boosting techniques, topologies, and applications. IEEE Trans Power Electron. March 2017;32(12):9143–78. doi:10.1109/TPEL.2017.2652318.
10. Fathabadi H. Novel high efficiency DC/DC boost converter for using in photovoltaic systems. Sol Energy. 2016;125(February):22–31. doi: 10.1016/j.solener.2015.11.047.
11. Colak I, Kabalci E, Bal G. Parallel DC-AC conversion system based on separate solar farms with MPPT control, IEEE 8th international conference on Power Electronics, 2011, Jeju, Korea. p.1469–75.
12. Kabalci Y, Kabalci E. The low cost voltage and current measurement device design for power converters. ECAI. 8th ed International Conference. Ploieşti: ROMÂNIA; 2016–. p. 1–6.
13. Devi ML, Chilambarasan M. Design and simulation of incremental conductance MPPT using self lift cuk converter. Vol. 2013. India: ICRESE; 2013. p. 105–11.
14. Abatan OA, Egunjobi AI, Musari AA, Oseni KJ, Edun AT, Sodunke MA. Design of 50-kVA single phase static inverter. Int J Adv Eng. 2014;4(August):319–24.
15. Colak I, Kabalci E. Developing a novel sinusoidal pulse width modulation (SPWM) technique to eliminate side band harmonics. IJEPES. 2013;44(1):861–71. doi: 10.1016/j.ijepes.2012.08.024.
16. Kahlane AEWH, Hassaine L, Kherchi M. LCL filter design for photovoltaic grid connected systems. Rev Energ Renouvelables SIENR. 2014:227–32.
17. Yong BH, Ramachandaramurthy VK. ’Harmonic Mitigation of grid connected 5MW solar PV using LCL filter,’ 3rd CEAT. Kuching, Malaysia; 2014. p. 1–6.
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19. Kivimäki J, Kolesnik S, Sitbon M, Suntio T, Kuperman A. Revisited perturbation frequency design guideline for direct fixed-step maximum Power Point tracking algorithms. IEEE Trans Ind Electron. 2017;64(6):4601–9. doi:10.1109/TIE.2017.2674589.
20. Elgendy MA, Zahawi B, Atkinson DJ. Operating characteristics of the P&O algorithm at high perturbation frequencies for standalone PV systems. IEEE Trans Energy Convers. 2015;30(1):189–98. doi: 10.1109/TEC.2014.2331391.
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nCurrently mobile has become our lifestyle, because of low price of housing automation and through DTMF. DTMF (dual tone multiple frequency) primarily based system contains 2 mobile phones, DTMF Decoder and UNL2003 main a part of the project. One mobile is employed as remote which can settled at way distance from home through that directions area unit felt occupation and another mobile is found reception act as a receiver. The management data area unit sent via the remote mobile as DTMF Tone, this DTMF tone is received by the mobile settled reception, the received DTMF tone is then decoded by DTMF Decoder IC MT8870. The output logic signal of Decoder is employed as input to the UNL2003. The UNL2003 to manage home appliances per output of DTMF Decoder. With the assistance of this technology, we will operate it at any place within the world and that we may management all the house appliances of the house. This technology can facilitate those folks that area unit physically challenged individuals. With this technology, they will operate all the house appliances simply with the assistance of mobile phones. Typically, once individuals exit of the house they forget to modify off the house appliances, and there could the wastage of power. The answer to the current drawback is DTMF (Dual Tone Multi Frequency) controlled home automation. We will management DTMF primarily based home automation with the assistance of mobile signal. Employing a DTMF technique the DTMF (Dual Tone Multi Frequency) decoder is connected to the relay that is controlled by the mobile by creating a telephone to the opposite mobile while not victimization microcontroller.n

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1. Ray PP. Internet of Things for smart agriculture: technologies practices and future road map in IOS J. Ambient Intell Smart Environ. 2017.
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3. Zanella A, Bui N, Castellani A, Vangelista L, Zorzi M. Internet of things for smart cities. IEEE Internet Things J. 2014;1(1):22–32. doi: 10.1109/JIOT.2014.2306328.
4. Piyare R, Tazil M. Bluetooth Based Home Automation System Using Cell phone 15th International Symposium on Consumer Electronics. IEEE Publications; 2011. p. 192–5.
5. Wei J. How Wearables Intersect with the Cloud and the Internet of Things: considerations for the developers of wearables. IEEE Con Electron Mag. 2014;3(3):53–6. doi: 10.1109/MCE.2014.2317895.
6. Haeil H, Jonghyun P, Yunchan C, Jae J. PC application remote control via mobile phone. In: KINTEX, Gyeonggido, Korea. International Conference on Control, Automation and Systems; 2010. October 27–30. p. 2290–4.
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nSmartMesh IP is an innovative way to connect smart devices with advanced network management and comprehensive security features. SmartMesh IP delivers reliable, scalable, and energy efficient wireless sensor connectivity. In recent years, SmartMesh IP has become the industry’s most energy- efficient wireless mesh sensing technology even in harsh and dynamically changing radio frequency (RF) environments. This paper proposes a SmartMesh IP network system that consists of a network manager and a group of motes. The network manager monitors and manages network performance and security, and exchanges data with a host application. The motes are the wireless nodes that have built-in sensors and can collect and relay data from/to other motes or from/to the network manager. The proposed system is implemented the system through hardware integration, firmware design, and software development, as well as system testing. Through various experiments, the software, firmware, and hardware platforms have been shown to be able to fully configure the SmartMesh IP devices and get them to perform real-world applications such as monitoring the environment temperature at different places within the SmartMesh IP network. By using internal or external temperature sensors, the platforms developed in C# programming have shown to successfully achieve the temperature data collection and the network topology viewing. The temperature data can be monitored by the system dynamically with respect to the real time. The developed network topology platform can be used to visualize the communicating nodes and the links among them in the SmartMesh IP network. The proposed design and implementation method can provide practical reference for the development and industrial application of SmartMesh IP networks.n

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1. J. Iannacci, RF-MEMS Technology for High-Performance Passives, 2017, IOP Publishing.
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10.1109/.2005.1467103
4. J.M. Kahn, R.H. Katz and K.S.J. Pister, “Mobile Networking for Smart Dust”, ACM/IEEE Intl.
Conf. on Mobile Computing and Networking (MobiCom 99), Seattle, WA, August 17-19, 1999.
5. M.A. Horton, S. Glaser, and N. Sitar, “Wireless Networks for Structural Health Monitoring and
Hazard Mitigation”, Proc. of the US-Europe Workshop on Sensors and Smart Structures
Technology, pp. 19-23, 2002.
6. IEEE 802.15.4-2003-IEEE Standard for Telecommunications and Information Exchange Between
Systems-LAN/MAN Specific Requirements-Part 15: Wireless Medium Access Control (MAC)
and Physical Layer (PHY) Specifications for Low Rate Wireless Personal Area Networks
(WPAN). https://standards.ieee.org/content/ieee-standards/en/standard/802_15_4-2003.html
7. K. Pister and L. Doherty, “TSMP: Time synchronized mesh protocol”, IASTED International
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8. J. Song, S. Han, A. Mok, D. Chen, M. Lucas, M. Nixon, and W. Pratt, “WirelessHART: Applying
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https://standards.ieee.org/standard/802_15_4e-2012.html
10. T. Watteyne, L. Doherty, J. Simon and K. Pister, “Technical Overview of SmartMesh IP,” 2013
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Computing, 2013, pp. 547-551, doi: 10.1109/IMIS.2013.97.
11. K. Brun-Laguna, A. L. Diedrichs, D. Dujovne, C. Taffernaberry, R. Léone, X. Vilajosana, and T.
Watteyne, “Using SmartMesh IP in Smart Agriculture and Smart Building applications”,
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03.010.
12. Y. Tanaka, B.H. Le, V. Kobayashi, C. Lopez, and T. Watteyne, “Demo: Blink–Room-Level
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Embedded Wireless Systems and Networks, pp. 198–199, Feb. 2020.
13. S. Gheorghiu, K. Nagy-Betegh, R. Molnar, and R. Grammenos, “WALLSY: The UWB and
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Publishing, March 2017.
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16. Analog Devices, DC9018B-B, SmartMesh IP RF Certified Evaluation/Development Mote.
Available: https://www.analog.com/en/design-center/evaluation-hardware-and-software/evaluati
on-boards-kits/dc9018b-b.html#eb-overview
17. M. Lutz, Learning Python, 5th Edition, June 2013, O’Reilly Media, Inc.
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https://www.iar.com/
19. Dust Networks, Inc., SmartMesh SDK-a Python package. Available: https://dustcloud.atlassian.
net/wiki/spaces/SMSDK/overview?homepageId=1015834

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