Challenges and Solutions for Engineering Applications on Smartphones
Abstract
:1. Introduction
2. Mobile Application Concept
3. State of the Art
3.1. Building Information Modeling (BIM)
3.2. Augmented Reality (AR)
3.3. Data Acquisition of Projects
3.4. Measurement and Data Collection
3.5. Computer-aided Design
3.6. Computer-aided Manufacturing (CAM)
3.7. Discussion about Engineering Smartphone Applications
4. Challenges
4.1. Optimizing Space Memory
4.1.1. User Graphical Interface
4.1.2. Data Management for Input/Output
4.2. Scientific Calculations
4.2.1. Memory Cost of Algorithms
4.2.2. Precision of Algorithms
4.3. Removal of Dependency on Programming Languages
5. Case Study: Engineering Application for Systems Control
5.1. Concept
5.2. Proposed Solution
5.2.1. Challenge: Optimizing Space Memory for User Graphical Interface
5.2.2. Challenge: Removal of Dependency on Programming Languages
5.3. Application
6. Case Study: Engineering Application for Composite Materials
6.1. Concept
6.2. Proposed Solution
6.2.1. Optimizing Space Memory for I/O Data Management
6.2.2. Challenge: Removal of Dependency on Programming Languages
6.3. Application
7. Case Study: Engineering Application for Finite Element Method
7.1. Concept
7.2. Proposed Solution
7.2.1. Optimizing Memory Costs for Scientific Calculations
7.2.2. Challenge: Precision of Algorithms in Scientific Calculations
7.3. Application
- Step 1: Discretizing the domain—this step involves subdividing the domain into elements and nodes;
- Step 2: Writing the element stiffness matrix—the element stiffness equations need to be written for each element in the domain;
- Step 3: Assembling the global stiffness matrix—this will be done using the direct stiffness approach;
- Step 4: Applying the boundary conditions—like supports, applied loads and displacements;
- Step 5: Solving the linear equations [A] [X] = [B];
- Step 6: Post-processing—to obtain the reactions, element forces and stresses.
8. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
- International Data Corporation, Smartphone Shipments Declined in Fourth Quarter but 2021 Was Still a Growth Year with a 5.7% Increase in Shipments; IDC Media Center: Needham, MA, USA, 2022.
- International Data Corporation, PC Demand Remained Strong in the Second Quarter Amid Early Signs That Market Conditions May Be Cooling, According to IDC; IDC Media Center: Needham, MA, USA, 2022.
- Taylor, P. Global Smartphone unit shipments 2009–2022. In Statista Technology & Telecommunications; Statista: Hamburg, Germany, 2023. [Google Scholar]
- GSMA. The Mobile Economy 2021; GSM Association: London, UK, 2021. [Google Scholar]
- Zaher, M.; Greenwood, D.; Marzouk, M. Mobile Augmented Reality Applications for Construction Projects. Constr. Innov. 2018, 18, 152–166. [Google Scholar] [CrossRef]
- Matlab. Matlab Documentation, Matlab Help; Matlab: Natick, MA, USA, 2022. [Google Scholar]
- Phongtraychak, A.; Dolgaya, D. Evolution of Mobile Applications. MATEC Web Conf. 2018, 155, 01027. [Google Scholar] [CrossRef]
- Hayfaa, M.; Subhi, Z.; Rizgar, Z.; Mohammed, S. A Comprehensive Study of Kernel (Issues and Concepts) in different operating systems. Asian J. Res. Comput. Sci. Inf. Technol. 2021, 8, 16–31. [Google Scholar]
- Department of Computer Science and Engineering. School of Computing, Mobile Application Development, Sathyabama, Institute of Science and Technology. Available online: https://www.sathyabama.ac.in/course-materials/mobile-application-development-0 (accessed on 4 March 2023).
- SCarvalho; Aniche, M.; Verssimo, J.; Durelli, R.; Gerosa, M. An empirical catalog of code smells for the presentation layer of Android apps. Empir. Softw. Eng. 2019, 24, 3546–3586. [Google Scholar] [CrossRef]
- Vishal, K.; Kushwaha, S. Mobile Application Development Research Based on Xamarin Platform. In Proceedings of the 4th International Conference on Computing Sciences (ICCS), Jalandhar, India, 30–31 August 2018; pp. 115–118. [Google Scholar]
- Swetina, J.; Lu, G.; Jacobs, P.; Ennesser, F.; Song, J. Toward a standardized common M2M service layer platform: Introduction to oneM2M. IEEE Wirel. Commun. 2014, 21, 20–26. [Google Scholar] [CrossRef]
- Qian, F.; Wang, Z.; Gerber, A.; Mao, Z.; Sen, S.; Spatscheck, O. Profiling resource usage for mobile applications: A cross-layer approach. In Proceedings of the 9th International Conference on Mobile Systems, Applications, and Services, Bethesda, MD, USA, 28 June 2011–1 July 2011; pp. 321–334. [Google Scholar]
- Chau, N.; Jung, S. Dynamic analysis with Android conatiner: Challenges and opportunities. Digit. Investig. 2018, 27, 38–46. [Google Scholar] [CrossRef]
- Welderufael, T.; Aleksy, M.; Andersson, K.; Lehtola, M. Mobile Computing Application for Industrial Field Service Engineering: A Case for ABB Service Engineers. In Proceedings of the 38th Annual IEEE Conference on Local Computer Networks, Sydney, NSW, Australia, 21–24 October 2013; pp. 188–193. [Google Scholar]
- Moustefaoui, G.; Tariq, F. Mobile Apps Engineering: Design, Development, Security, and Testing; CRC Press: Boca Raton, FL, USA, 2018. [Google Scholar]
- Pei-Huang, D.; Naai-Jung, S. BIM-Based AR Maintenance System (BARMS) as an Intelligent Instruction Platform for Complex Plumbing Facilities. Appl. Sci. 2019, 9, 1592. [Google Scholar]
- Williams, G.; Gheisari, M.; Chen, P. An efficient BIM Translation to Mobile augmented reality applications. J. Manag. Eng. 2015, 31, A4014009. [Google Scholar] [CrossRef]
- VisualLive, Mobilive, Mixed Reality (AR) for iOS/Android, VisualLive. Available online: https://visuallive.nl/mobilive-mixed-reality-ar-for-ios-android/ (accessed on 5 March 2023).
- Meza, S.; Turk, Z.; Dolenc, M. Measuring the potential of augmented reality in civil engineering. Adv. Eng. Softw. 2015, 90, 1–10. [Google Scholar] [CrossRef]
- Golpavar, F. Assessment of Collaborative Decision-Making in Design Development. Master’s Thesis, University of British Columbia, Vancouver, BC, Canada, 2006. [Google Scholar]
- Shakil, A. A Review on Using Opportunities of Augmented Reality and Virtual Reality in Construction Project Management. OTMC Int. J. 2019, 10, 1839–1852. [Google Scholar]
- Yoora, P.; Hyojoo, S.; Changwan, K. Investigating the determinants of construction professionals’ acceptance of web-based training: An extension of the technology acceptance model. Autom. Constr. 2012, 22, 377–386. [Google Scholar]
- Nazar, A.; Jiao, P.; Zhang, Q.; Egbe, K.; Alavi, A. A new structural health monitoring approach based on smartphone measurements of magnetic field intensity. IEEE Instrum. Meas. Mag. 2021, 24, 49–58. [Google Scholar] [CrossRef]
- Park, D.H.; Heo, J.M.; Jeong, W.; Yoo, Y.H.; Park, B.J. Smartphone-Based VOC Sensor Using Colorimetric Polydiacetylenes. ACS Appl. Mater. Interfaces 2018, 10, 5014–5021. [Google Scholar] [CrossRef]
- Minichiello, A.; Armijo, D.; Mukherjee, S.; Caldwell, L.; Kulyukin, V.; Truscott, T.; Elliott, J.; Bhouraskar, A. Developing a mobile application-based particle image velocimetry tool for enhanced teaching and learning in fluid mechanics: A design-based research approach. Comput. Appl. Eng. Educ. 2020, 29, 517–537. [Google Scholar] [CrossRef]
- De Oliveira, M.T.; Maija, M.; Leslie, M.; Terhi, L.; Sarang, T.; Ville, L. Towards tropospheric delay estimation using GNSS smartphone receiver network. Adv. Space Res. 2021, 68, 4794–4805. [Google Scholar] [CrossRef]
- Kanetaki, Z.; Stergiou, C.; Bekas, G.; Kanetaki, E. Machine Learning and Statistical Analysis applied on Mechanical Engineering CAD course: A Case Study During ERTE Pahse in the Context of Higher Education. In Proceedings of the 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies, Istanbul, Turkey, 22–24 October 2020. [Google Scholar]
- Modic, E. Linear Bearing CAD Models on the Fly; Today’s Medical Development: Valley View, OH, USA, 2018. [Google Scholar]
- Olivotti, D.; Dreyer, S.; Kolsch, P.; Herder, C.; Breitner, M.; Aurich, J. Realizing availability-oriented business models in the capital goods industry. In Proceedings of the 10th CIRP Conference on Industrial Product-Service Systems, IPS2 2018, Linköping, Sweden, 29–31 May 2018; pp. 29–31. [Google Scholar]
- Kahriman, F.; Liland, K. SelectWave: A graphical user interface for wavelength selection and spectral data analysis. Chenometrics Intell. Lab. Syst. 2021, 212, 104275. [Google Scholar] [CrossRef]
- Zanfardimo, M.; Castaldo, R. MuSA: A graphical user interface for multi-OMICs data integration in radiogenomic studies. Sci. Rep. 2021, 11, 1550. [Google Scholar] [CrossRef]
- Carruth, D.; Hudson, C.; Fox, A.; Deb, S. User Interface for an Immersive Virtual Reality Greenhouse for Training Precision Agriculture. In HCII 2020: Virtual, Augmented and Mixed Reality. Industrial and Everyday Life Applications; Springer International Publishing: Berlin/Heidelberg, Germany, 2020. [Google Scholar]
- Alturki, R.; Gay, V. Usability Attributes for Mobile Applications, a Systematic review; Faculty of Engineering and Information Technology, University of Technology Sidney: Ultimo, NSW, Australia, 2018. [Google Scholar]
- Punchoojit, L. Usability Studies on Mobile User Interface Design Patterns: A Systematic Literature Review. Adv. Hum.-Comput. Interact. 2017, 2017, 6787504. [Google Scholar] [CrossRef]
- Bennett, K.; Nagy, A.; Flash, J. Visual Display, Handbook of Human Factors and Ergonomics; John Wiley & Sons: Hoboken, NJ, USA, 2012. [Google Scholar]
- Abdalha, A.; Muasaad, A. A study of the interface usability issues of mobile learning applications for smartphones from the user’s perspective. In Proceedings of the International Journal on Integrating Technology in Education (IJITE), Lyon, France, 19–22 May 2008; Volume 3. [Google Scholar]
- Deelman, E.; Chervenak, A. Data Management Challenges of Data-Intensive Scientific Workflows. In Proceedings of the 2008 Eighth IEEE International Symposium on Cluster Computing and the Grid, Lyon, France, 19–22 May 2008. [Google Scholar]
- Sosa, J.; Thomas, P.; Delia, L.; Caseres, J. Mobile Application Development Approaches: A Comparative Analysis on the Use of Storage Space. In Argentine Congress of Computer Science XXIV; SEDICI: Seaford, UK, 2018. [Google Scholar]
- Vandenbrouke, K.; Ferreira, D.; Goncalvez, J. Mobile cloud storage: A contextual experience. In Proceedings of the 16th International Conference on Human-Computer Interaction with Mobile Devices & Services, Toronto, ON, Canada, 23–26 September 2014. [Google Scholar]
- Li, C.; Bai, J.; Tang, J. Joint optimization of data placement and scheduling for improving user experience in edge computing. J. Parallel Distrib. Comput. 2019, 125, 93–105. [Google Scholar] [CrossRef]
- Carroll, A.; Heiser, G. An Analysis of Power Consumption in a Smartphone. In Proceedings of the 2010 USENIX Conference on USENIX Annual Technical Conference, Boston, MA, USA, 22–25 June 2010. [Google Scholar]
- Ataeeshojai, M.; Elliott, R.; Krzymien, W.; Tellambura, C.; Maljevic, I. Iterative Matrix Inversion Methods for Precoding in Cell-Free Massive MIMO Systems. IEEE Trans. Veh. Technol. 2022, 71, 11972–11987. [Google Scholar] [CrossRef]
- Albreem, M. Approximate Matrix Inversion Methods for Massive MIMO Detectors. In Proceedings of the IEEE 23rd International Symposium on Consumer Technologies (ISCT), Ancona, Italy, 19–21 June 2019. [Google Scholar]
- Wu, J.; Bose, A. A new successive relaxation scheme for the W-matrix solution method on a shared memory parallel computer. IEEE Trans. Power Syst. 1996, 11, 233–238. [Google Scholar]
- Williamson, D.; Shmoys, D. The Design of Approximation Algorithms; Cambridge University Press: Cambridge, UK, 2011. [Google Scholar]
- Hanrahan, G.; Patil, D. Chemometrics & Statistics; Multivariate Calibration Techniques, Encyclopedia of Analytical Science, 7th ed.; Elsevier: Amsterdam, The Netherlands, 2005. [Google Scholar]
- Steinwart, I.; Hush, D.; Scovel, C. Optimal Rates for Regularized Least Squares Regression; Los Alamos National Laboratory: Los Alamos, NM, USA, 2009. [Google Scholar]
- Cooper, K.; Harvey, T. Compiler-controlled memory. ACM SIGOPS Oper. Syst. Rev. 1998, 32, 2–11. [Google Scholar] [CrossRef]
- Ou, P.; Desmky, B. Towards understanding the costs of avoiding out-of-thin-air results. In Proceedings of the ACM on Programming Languages, Boston, MA, USA, 24 October 2018; Volume 2. [Google Scholar]
- Gotz, S.; Tichy, M.; Kehrer, T. Dedicated Model Transformation Languages vs. General-Purpose Languages: A Historical Perspective on ATL vs. Java; Science & Technology Publications: Setúbal, Portugal, 2021. [Google Scholar]
- Hopner, S.; Kehrer, T.; Tichy, M. Contrasting dedicated model transformation languages versus general purpose languages: A historical perspective on ATL versus Java based on complexity and size. Softw. Syst. Model. 2022, 21, 805–837. [Google Scholar] [CrossRef]
- Gotz, S.; Tichy, M.; Kehrer, T. Claimed advantages and disadvantages of (dedicated) model transformation languages: A systematic literature review. Softw. Syst. Model. 2021, 20, 469–503. [Google Scholar] [CrossRef]
- Van Den Brouke, B.; Tumer, F.; Lomov, S.; Verpoest, I.; De Luka, P.; Dufort, L. Micro–macro structural analysis of textile composite parts: Case study. In Proceedings of the 25th International SAMPE Europe Conference, Paris, France, 30 March–1 April 2004. [Google Scholar]
- Lomov, S.; Van Den Brouke, B.; Tumer, F.; Verpoest, I.; De Luka, P.; Dufort, L. Micro–macro structural analysis of textile composite parts. In Proceedings of the ECCM-11, Rodos, Greece, 31 May–3 June 2004; pp. 194–199. [Google Scholar]
- Gommers, B.; Verpoest, I.; Van Houtte, P. The Mori–Tanaka method applied to textile composite materials. Acta Mater. 1998, 46, 2223–2235. [Google Scholar] [CrossRef]
- Lomov, S.; Truevtzev, N. A software package for the prediction of woven fabrics geometrical and mechanical properties. Fibres Text East Eur. 1995, 3, 49–52. [Google Scholar]
- Belov, E.; Lomov, S.; Verpoest, I.; Peeters, T.; Roose, D.; Parnas, R. Modelling of permeability of textile reinforcements: Modelling of permeability of textile reinforcements. Compos. Sci. Tecnol. 2004. [Google Scholar] [CrossRef]
- Carvelli, V.; Chi, T.; Larosa, M.; Lomov, S.; Poggi, C.; Ranz, D. Experimental and numerical determination of the mechanical properties of multi-axial multiply composites. In Proceedings of the ECCM-11, Rodos, Greece, 31 May–3 June 2004. [Google Scholar]
- Lomov, S.; Mikolanda, T. Textile Virtual Reality. In Proceedings of the TechTextile Symposium, Frankfurt, Germany, 6–9 June 2005. [Google Scholar]
- Verspoest, I.; Lomov, S. Virtual Textile Composites Software: Integration with micromechanical, permeability and structural analysis. Compos. Sci. Technol. 2005, 65, 2563–2574. [Google Scholar] [CrossRef]
- ASTM. A Standard Test Method for Tensile Properties of Polymer Matrix Composite Materials; ASTM: West Conshohocken, PA, USA, 2008. [Google Scholar]
- Blacklock, M.; Shaw, J.; Zok, F.; Cox, B. Virtual Specimens for analyzing strain distributions in textile ceramic composite. Compos. Part A Appl. Sci. Manuf. 2016, 85, 40–51. [Google Scholar] [CrossRef]
- Kaddaha, M.; Younes, R.; Lafon, P. New Geometrical Modelling for 2D Fabric and 2.5D Interlock Composites. Textiles 2022, 2, 142–161. [Google Scholar] [CrossRef]
- Bathe, K. Finite Element Procedures; Prentice-Hall: Englewood Cliffs, NJ, USA, 1996. [Google Scholar]
- Smith, I.; Griffiths, D. Programming the Finite Element Method; Wiley: Chichester, UK, 1998. [Google Scholar]
- Zimmerman, T.; Dubois, Y.; Bomme, P. Object-oriented Finite Element Programming: I. Governing Principles. Comput. Methods Appl. Mech. Eng. 1992, 98, 291–303. [Google Scholar] [CrossRef]
- Zimmerman, T.; Dubois, Y.; Bomme, P. Object-oriented Finite Element Programming: II. A Prototype Program in Smalltalk. Comput. Methods Appl. Mech. Eng. 1992, 98, 361–397. [Google Scholar] [CrossRef]
- Zimmerman, T.; Dubois, Y.; Bomme, P. Object-oriented Finite Element Programming: II. An Efficient Implementation in C++. Comput. Methods Appl. Mech. Eng. 1993, 108, 165–183. [Google Scholar]
- Donescu, P.; Laursen, T. A Generalized Object-Oriented Approach to Solving Ordinary and Partial Differential Equations Using Finite Elements. Finite Elements Anal. Des. 1996, 22, 93–107. [Google Scholar] [CrossRef]
- Nikishkov, G. Object Oriented Design of a Finite Element Code in Java. Comput. Model. Eng. Sci. 2006, 11, 81–90. [Google Scholar]
- Macdonald, B. An Object-Oriented Smarpthone Application for Structural Finite Element Analysis. Int. J. Adv. Comput. Sci. Appl. 2014, 5, 59–66. [Google Scholar]
- Calcul Des Structures Par Elements Finis Legay PDF. Available online: http://antoinelegay.free.fr/Calcul_des_structures_par_elements_finis_Legay.pdf (accessed on 20 April 2023).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Khoury, A.; Kaddaha, M.A.; Saade, M.; Younes, R.; Outbib, R.; Lafon, P. Challenges and Solutions for Engineering Applications on Smartphones. Software 2023, 2, 350-376. https://doi.org/10.3390/software2030017
Khoury A, Kaddaha MA, Saade M, Younes R, Outbib R, Lafon P. Challenges and Solutions for Engineering Applications on Smartphones. Software. 2023; 2(3):350-376. https://doi.org/10.3390/software2030017
Chicago/Turabian StyleKhoury, Anthony, Mohamad Abbas Kaddaha, Maya Saade, Rafic Younes, Rachid Outbib, and Pascal Lafon. 2023. "Challenges and Solutions for Engineering Applications on Smartphones" Software 2, no. 3: 350-376. https://doi.org/10.3390/software2030017