i-manager Publications

i-manager's Journal on Future Engineering and Technology (JFET)

Current Issue Vol. 20 Issue 1

Biomaterial Strategies for Immune System Enhancement and Tissue Healing
Qualitative and Quantitative Performance Optimization of Simple Gas Turbine Power Plant using Three Different Types of Fuel
Efficient Shopping: RFID-Powered Cart with Automated Billing System
Medical Drone System for Automated External Defibrillator Shock Delivery for Cardiac Arrest Patients
A Critical Review on Biodiesel Production, Process Parameters, Properties, Comparison and Challenges
Review on Deep Learning Based Image Segmentation for Brain Tumor Detection

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Volume 18 Issue 4 July - September 2023

Article

Decarbonization: Pathways for a Sustainable Future

Dr. Ushaa Eswaran* , Vishal Eswaran**

* Indira Institute of Technology & Sciences, Markapur, India.

** CVS Health, Dallas, Texas, United States.

Eswaran, U., and Eswaran, V. (2023). Decarbonization: Pathways for a Sustainable Future. i-manager’s Journal on Future Engineering & Technology, 18(4), 1-5. https://doi.org/10.26634/jfet.18.4.20018

Abstract

Decarbonization, the process of reducing carbon emissions, is critical for mitigating climate change and enabling the transition to a sustainable future. This paper examines decarbonization strategies across the energy, transportation, buildings and industrial sectors. A mix of quantitative and qualitative methodologies, including data analysis, modeling and policy analysis are utilized. Key findings show that while decarbonization requires ambitious policies and investments, the goals of net-zero emissions are technologically and economically feasible through clean electrification, energy efficiency, carbon capture and natural climate solutions. Comprehensive decarbonization must occur rapidly across all sectors to avoid the worst climate change impacts.

References

[1]. Geels, F. W., Berkhout, F., & Van Vuuren, D. P. (2016). Bridging analytical approaches for low-carbon transitions. Nature Climate Change, 6(6), 576-583.

[2]. Griscom, B. W., Adams, J., Ellis, P. W., Houghton, R. A., Lomax, G., Miteva, D. A., ... & Fargione, J. (2017). Natural climate solutions. Proceedings of the National Academy of Sciences, 114(44), 11645-11650.

[3]. International Energy Agency. (2021). Net Zero by 2050 - A Roadmap for the Global Energy Sector.

[4]. IPCC. (2018). Global Warming of 1.5°C.

[5]. Johnsson, F., Kjärstad, J., & Rootzén, J. (2019). The threat to climate change mitigation posed by the abundance of fossil fuels. Climate Policy, 19(2), 258-274.

[6]. Larson, E., Greig, C., Jenkins, J., Mayfield, E., Pascale, C., Zhang, C., & Williams, R. (2021). Net-Zero America: Potential Pathways, Infrastructure, and Impacts.

[7]. Material Economics. (2018). The Circular Economy -a Powerful Force for Climate Mitigation.

[8]. Material Economics. (2019). Industrial Transformation 2050 - Pathways to Net-Zero Emissions from EU Heavy Industry.

[9]. Rockström, J., Gaffney, O., Rogelj, J., Meinshausen, M., Nakicenovic, N., & Schellnhuber, H. J. (2017). A roadmap for rapid decarbonization. Science, 355(6331), 1269-1271.

[10]. Rogelj, J., Popp, A., Calvin, K. V., Luderer, G., Emmerling, J., Gernaat, D., ... & Strefler, J. (2018). Scenarios towards limiting global mean temperature increase below 1.5 C. Nature Climate Change, 8(4), 325-332.

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Research Paper

Optimization of Temperature, Humidity and Airflow in African Indigenous Vegetable (AIV) Greenhouse

Tendai Talent Ngwarati* , Kevin Mtondo, Francis Hove*, Sibanda Simelokuhle****

*-**** Marondera University of Agriculture Science and Technology, Marondera, Zimbabwe.

Ngwarati, T. T., Mtondo, K., Hove, F., and Simelokuhle, S. (2023). Optimization of Temperature, Humidity and Airflow in African Indigenous Vegetable (AIV) Greenhouse. i-manager’s Journal on Future Engineering & Technology, 18(4), 6-15. https://doi.org/10.26634/jfet.18.4.19760

Abstract

This research presents a novel approach for effectively optimizing growth rate and yield in a greenhouse. With the market demanding higher-quality standards, greenhouse cultivation is becoming increasingly sophisticated and competitive. However, the implementation of protected cultivation systems is expensive. Therefore, it is crucial for African Indigenous Vegetable (AIV) greenhouses to be optimized under stringent production conditions to remain competitive. Currently, greenhouse management decisions are categorized into various levels, ranging from real-time control to environmental optimization and seasonal market planning. The primary objective of our research is to optimize greenhouse conditions, specifically temperature, humidity, and airflow, at the Agro Industrial Park (AIP). To accomplish this, Design-Expert software, which is a computer-based tool equipped with contemporary statistical models and tools, was employed to accurately estimate the required ranges of microclimate parameters that should be maintained to achieve optimal growth rate and yield. By utilizing this approach, this study aimed to provide valuable insights and recommendations for enhancing greenhouse productivity. Ultimately, this study contributes to the development and advancement of AIV greenhouses by offering practical solutions to optimize microclimate conditions, resulting in improved growth and increased yield.

References

[1]. Alwan, G. M. (2016). Optimization Techniques for Research and Design. Missouri University of Science and Technology, (pp. 1-18).

[2]. Ayua, E. O. (2016). Post-Harvest Handling and Value Addition of African Indigenous Vegetables in Western Kenya (Doctoral dissertation, University of Eldoret).

[3]. Campen, J. B., De Zwart, H. F., Al Hammadi, M., Al Shrouf, A., & Dawoud, M. (2018). Climatization of a closed greenhouse in the Middle East. Acta Horticulture, 1227, 53–59.

[4]. Dalai, S., Tripathy, B., Mohanta, S., Sahu, B., & Palai, J. B. (2020). Green-houses: Types and structural components. In Protected Cultivation and Smart Agriculture (pp. 9-17).

[5]. Demeke, M., Pangrazio, G., & Maetz, M. (2009). Country Responses to the Food Security Crisis: Nature and Preliminary Implications of the Policies Pursued. FAO.

[6]. Omid, M. (2004). A computer-based monitoring system to maintain optimum air temperature and relative humidity in greenhouses. International Journal of Agriculture & Biology, 6(6), 1084-1088.

[7]. Pandey, V., Pant, M., & Snasel, V. (2022). Blockchain technology in food supply chains: Review and bibliometric analysis. Technology in Society, 69, 101954.

[8]. Ramírez-Arias, A., Rodríguez, F., Guzmán, J. L., Arahal, M. R., Berenguel, M., & López, J. C. (2005). Improving efficiency of greenhouse heating systems using model predictive control. IFAC Proceedings Volumes, 38(1), 40-45.

[9]. Siveter, R., Castañeda, J., Emmert, A., Lee, A., Juez, J. M., Stephenson, T., ... & Verduzco, L. (2014, March). The expanding role of natural gas: Comparing life-cycle greenhouse gas emissions. In SPE International Conference on Health, Safety, and Environment. OnePetro.

[10]. Toklu, Y. C. (2012). Optimization in structural analysis and design. Structures Congress 2009.

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Research Paper

ANN Modeling of Lead Adsorption from Water using Biowaste Material as Adsorbent

D. Krishna* , S. V. A. R. Sastry, D. V. Padma*

, Department of Chemical Engineering, M.V.G.R. College of Engineering, Vizianagaram, Andhra Pradesh, India.

Department of Chemical Engineering, Harcourt Butler Technical University, Kanpur, Uttar Pradesh, India.

Krishna, D., Sastry, S. V. A. R., and Padma, D. V. (2023). ANN Modeling of Lead Adsorption from Water using Biowaste Material as Adsorbent. i-manager’s Journal on Future Engineering & Technology, 18(4), 16-25. https://doi.org/10.26634/jfet.18.4.19909

Abstract

This research employed an Artificial Neural Network (ANN) approach to model the adsorption of lead from water using biowaste material as an adsorbent. To develop the ANN model, 39 experimental data point values for training and 15 experimental data point values for testing were used. The model involved the use of a tansigmoid transfer function for the input, purelin for the output, and a hidden layer consisting of 19 neurons to minimize the square error. The highest percentage of lead removal was achieved with optimal adsorption parameters (i.e., pH, concentration of lead, and biosorbent dosage). The experimental data closely matched the predicted values obtained from the ANN model with a R2 (regression coefficient) of 0.988. To determine the maximum percentage of lead removal and the optimal adsorption parameters, a pattern-search approach using a genetic algorithm was employed. In this study, adsorbent powder was prepared using biowaste materials, such as Borasus flabellifer coir.

References

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[2]. Acharya, S. (2013). Lead between the lines. Nature Chemistry, 5, 894.

[3]. Ara, A., & Usmani, J. A. (2015). Lead toxicity: A review. Interdisciplinary Toxicology, 8(2), 55-64.

[4]. Azimi, A., Azari, A., Rezakazemi, M., & Ansarpour, M. (2017). Removal of heavy metals from industrial wastewaters: A review. ChemBioEng Reviews, 4(1), 37-59.

[5]. Buckles, B. P., Petry, F. E., & Kuester, R. L. (1990, November). Schema survival rates and heuristic search in genetic algorithms. In [1990] Proceedings of the 2nd International IEEE Conference on Tools for Artificial Intelligence (pp. 322-327). IEEE.

[6]. Bundy, A. (1997). Artificial intelligence techniques. In Artificial Intelligence Techniques: A Comprehensive Catalogue (pp. 1-129). Springer, Berlin, Heidelberg.

[7]. Charkiewicz, A. E., & Backstrand, J. R. (2020). Lead toxicity and pollution in Poland. International Journal of Environmental Research and Public Health, 17(12), 4385.

[8]. Dursun, S., & Pala, A. (2007). Lead pollution removal from water using a natural zeolite. Journal of International Environmental Application and Science, 7(1), 11-19.

[9]. Kardam, A., Raj, K. R., Arora, J. K., & Srivastava, S. (2011). ANN modeling on predictions of biosorption efficiency of zea mays for the removal of Cr (III) and Cr (VI) from waste water. International Journal of Mathematics Trends & Technology (pp. 23-29).

[10]. Krishna, D., & Sree, R. P. (2013). Artificial neural network and response surface methodology approach for modeling and optimization of chromium (VI) adsorption from waste water using Ragi husk powder. Indian Chemical Engineer, 55(3), 200-222.

[11]. Krishna, D., & Sree, R. P. (2014). Artificial Neural Network (ANN) Approach for modeling chromium (VI) adsorption from aqueous solution using a Borasus Flabellifer coir powder. International Journal of Applied Science and Engineering, 12(3), 177-192.

[12]. Krishna, D., Kumar, G. S., & Raju, D. P. (2018). Effect of various parameters on biosorption of lead (II) by ragi husk powder. International Journal of Current Engineering and Scientific Research, 5(12), 1-14.

[13]. Krishna, D., Kumar, G. S., & Raju, D. P. (2019a). Equilibrium kinetic and isotherm studies for the removal of lead (II) From wastewater using Borasus flabellifer coir powder. i-manager's Journal on Future Engineering and Technology, 15(2), 37-47.

[14]. Krishna, D., Kumar, G. S., & Raju, D. R. P. (2019b). Optimization of process parameters for the removal of chromium (VI) from waste water using mixed adsorbent. International Journal of Applied Science and Engineering, 16(3), 187-200.

[15]. Lo, W., Chua, H., Lam, K. H., & Bi, S. P. (1999). A comparative investigation on the biosorption of lead by filamentous fungal biomass. Chemosphere, 39(15), 2723-2736.

[16]. Mohammed, A. K., Ali, S. A., Najem, A. M., & Ghaima, K. K. (2013). Effect of some factors on biosorption of lead by dried leaves of water hyacinth (Eichhornia crassipes). International Journal of Pure and Applied Sciences and Technology, 17(2), 72-78.

[17]. Mousavi, H. Z., Hosseynifar, A., Jahed, V., & Dehghani, S. A. M. (2010). Removal of lead from aqueous solution using waste tire rubber ash as an adsorbent. Brazilian Journal of Chemical Engineering, 27, 79-87.

[18]. Oboh, O. I., & Aluyor, E. O. (2008). The removal of heavy metal ions from aqueous solutions using sour sop seeds as biosorbent. African Journal of Biotechnology, 7(24), 4508-4511.

[19]. Prakash, N., Manikandan, S. A., Govindarajan, L., & Vijayagopal, V. (2008). Prediction of biosorption efficiency for the removal of copper (II) using artificial neural networks. Journal of Hazardous Materials, 152(3), 1268-1275.

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[21]. Turan, N. G., Mesci, B., & Ozgonenel, O. (2011). Artificial Neural Network (ANN) approach for modeling Zn (II) adsorption from leachate using a new biosorbent. Chemical Engineering Journal, 173(1), 98-105.

[22]. Yarkandi, N. H. (2014). Removal of lead (II) from waste water by adsorption. International Journal of Current Microbiology and Applied Sciences, 3(4), 207-228.

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Research Paper

Design and Evaluation of Solar Power Based Wireless Power Transfer System with Road-Embedded Transmitter Coil for Dynamic Charging of Electric Vehicle

Shraddha Kaushik* , Pooja Nuruti, Shreya Sarangi*, Manu Pandey**, Somesh Kumar Sahu*, Sarabjeet Singh****

*-****** Department of Electrical Engineering, Bhilai Institute of Technology, Chhattisgarh, India.

Kaushik, S., Nuruti, P., Sarangi, S., Pandey, M., Sahu, S. K., and Singh, S. (2023). Design and Evaluation of Solar Power Based Wireless Power Transfer System with Road-Embedded Transmitter Coil for Dynamic Charging of Electric Vehicle. i-manager’s Journal on Future Engineering & Technology, 18(4), 26-36. https://doi.org/10.26634/jfet.18.4.19477

Abstract

The transportation sector is moving away from conventional fossil fuel-powered vehicles towards electric mobility. Petrol and diesel-powered vehicles contribute significantly to the carbon footprint. Consequently, the use of electric vehicles helps to reduce reliance on internal combustion engines and promotes zero emissions. Electric vehicles are expected to become the mainstream mode of transportation with the development of robust charging infrastructure. This research proposed an innovative solution for wirelessly charging electric vehicles using dynamic wireless power transfer, which incorporates solar panels for feasible charging. The system relies on resonant inductive power transfer between the coils installed beneath the road surface and a receiver coil placed on the vehicle. The proposed system was simulated in MATLAB, and an experimental validation was conducted using a hardware setup. The overall system showcases power transmission to charge the vehicle's battery while in motion, eliminating the need to wait for a full battery charge.

References

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[4]. Hui, S. Y. (2013). Planar wireless charging technology for portable electronic products and Qi. Proceedings of the IEEE, 101(6), 1290-1301.

[5]. Koot, M., Kessels, J. T., De Jager, B., Heemels, W. P. M. H., Van den Bosch, P. P. J., & Steinbuch, M. (2005). Energy management strategies for vehicular electric power systems. IEEE Transactions on Vehicular Technology, 54(3), 771-782.

[6]. Lin, Z., Li, J. M., & Dong, J. (2014). Dynamic wireless power transfer: Potential impact on plug-in electric vehicle adoption. SAE International.

[7]. Lukic, S., & Pantic, Z. (2013). Cutting the cord: Static and dynamic inductive wireless charging of electric vehicles. IEEE Electrification Magazine, 1(1), 57-64.

[8]. Mi, C. C., Buja, G., Choi, S. Y., & Rim, C. T. (2016). Modern advances in wireless power transfer systems for roadway powered electric vehicles. IEEE Transactions on Industrial Electronics, 63(10), 6533-6545.

[9]. Mohamed, A. A., Lashway, C. R., & Mohammed, O. (2017). Modeling and feasibility analysis of quasidynamic WPT system for EV applications. IEEE Transactions on Transportation Electrification, 3(2), 343-353.

[10]. Panchal, C., Stegen, S., & Lu, J. (2018). Review of static and dynamic wireless electric vehicle charging system. Engineering Science and Technology, An International Journal, 21(5), 922-937.

[11]. Prasad, B. R. V., Geethanjali, M., Sonia, M., Ganeesh, S., & Krishna, P. S. (2022). Solar wireless electric vehicle charging system. International Journal of Scientific Research in Engineering and Management, 6(6), 1-7.

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Review Paper

Exploring the Potential of Solar and Wind Energy

Bisman Singh* , Bhawna, Santosh Kumar*

- Department of Computer Science & Engineering, Chandigarh Group of Colleges, Landran, Mohali, Punjab, India.

Department of Mechanical Engineering, Chandigarh Group of Colleges, Landran, Mohali, Punjab, India.

Singh, B., Bhawna, and Kumar, S. (2023). Exploring the Potential of Solar and Wind Energy. i-manager’s Journal on Future Engineering & Technology, 18(4), 37-49. https://doi.org/10.26634/jfet.18.4.19735

Abstract

In recent years, there has been significant interest in renewable energy sources, such as solar and wind energy, as sustainable and environmentally friendly alternatives to fossil fuels. The efficiency of these sources play a crucial role in determining their viability as replacements for the traditional energy sources. This review aims to investigate the efficiency of solar and wind energy, considering their current utilization, technological advancements, and future prospects. The analysis also assesses the financial and ecological implications of renewable energy and explores potential strategies for enhancing its efficiency. The findings of this study will contribute to future efforts to establish a sustainable and environmentally conscious energy landscape.

References

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i-manager's Journal on Future Engineering and Technology (JFET)

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Volume 18 Issue 4 July - September 2023

Decarbonization: Pathways for a Sustainable Future

Dr. Ushaa Eswaran* , Vishal Eswaran**

* Indira Institute of Technology & Sciences, Markapur, India. ** CVS Health, Dallas, Texas, United States.

Eswaran, U., and Eswaran, V. (2023). Decarbonization: Pathways for a Sustainable Future. i-manager’s Journal on Future Engineering & Technology, 18(4), 1-5. https://doi.org/10.26634/jfet.18.4.20018

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Optimization of Temperature, Humidity and Airflow in African Indigenous Vegetable (AIV) Greenhouse

Tendai Talent Ngwarati* , Kevin Mtondo**, Francis Hove***, Sibanda Simelokuhle****

*-**** Marondera University of Agriculture Science and Technology, Marondera, Zimbabwe.

Ngwarati, T. T., Mtondo, K., Hove, F., and Simelokuhle, S. (2023). Optimization of Temperature, Humidity and Airflow in African Indigenous Vegetable (AIV) Greenhouse. i-manager’s Journal on Future Engineering & Technology, 18(4), 6-15. https://doi.org/10.26634/jfet.18.4.19760

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ANN Modeling of Lead Adsorption from Water using Biowaste Material as Adsorbent

D. Krishna* , S. V. A. R. Sastry**, D. V. Padma***

*,*** Department of Chemical Engineering, M.V.G.R. College of Engineering, Vizianagaram, Andhra Pradesh, India. ** Department of Chemical Engineering, Harcourt Butler Technical University, Kanpur, Uttar Pradesh, India.

Krishna, D., Sastry, S. V. A. R., and Padma, D. V. (2023). ANN Modeling of Lead Adsorption from Water using Biowaste Material as Adsorbent. i-manager’s Journal on Future Engineering & Technology, 18(4), 16-25. https://doi.org/10.26634/jfet.18.4.19909

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Design and Evaluation of Solar Power Based Wireless Power Transfer System with Road-Embedded Transmitter Coil for Dynamic Charging of Electric Vehicle

Shraddha Kaushik* , Pooja Nuruti**, Shreya Sarangi***, Manu Pandey****, Somesh Kumar Sahu*****, Sarabjeet Singh******

*-****** Department of Electrical Engineering, Bhilai Institute of Technology, Chhattisgarh, India.

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Exploring the Potential of Solar and Wind Energy

Bisman Singh* , Bhawna**, Santosh Kumar***

*-** Department of Computer Science & Engineering, Chandigarh Group of Colleges, Landran, Mohali, Punjab, India. *** Department of Mechanical Engineering, Chandigarh Group of Colleges, Landran, Mohali, Punjab, India.

Singh, B., Bhawna, and Kumar, S. (2023). Exploring the Potential of Solar and Wind Energy. i-manager’s Journal on Future Engineering & Technology, 18(4), 37-49. https://doi.org/10.26634/jfet.18.4.19735

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* Indira Institute of Technology & Sciences, Markapur, India.

** CVS Health, Dallas, Texas, United States.

Tendai Talent Ngwarati* , Kevin Mtondo, Francis Hove*, Sibanda Simelokuhle****

D. Krishna* , S. V. A. R. Sastry, D. V. Padma*

, Department of Chemical Engineering, M.V.G.R. College of Engineering, Vizianagaram, Andhra Pradesh, India.

Department of Chemical Engineering, Harcourt Butler Technical University, Kanpur, Uttar Pradesh, India.

Shraddha Kaushik* , Pooja Nuruti, Shreya Sarangi*, Manu Pandey**, Somesh Kumar Sahu*, Sarabjeet Singh****

Bisman Singh* , Bhawna, Santosh Kumar*

- Department of Computer Science & Engineering, Chandigarh Group of Colleges, Landran, Mohali, Punjab, India.

Department of Mechanical Engineering, Chandigarh Group of Colleges, Landran, Mohali, Punjab, India.