Model-Driven Engineering and Creative Arts Approach to Designing Climate Change Response System for Rural Africa: A Case Study of Adum-Aiona Community in Nigeria
Emmanuel Okewu
Centre for Information Technology and Systems, University of Lagos, Lagos (Nigeria)
Sanjay Misra
Department of Computer and Information Sciences, Covenant University, Ota, Nigeria; Atilim University, Ankara, Turkey (Nigeria)
Jonathan Okewu
Department of Visual and Creative Arts, Federal University, Lafia (Nigeria)
Abstract
Experts at the just concluded climate summit in Paris (COP21) are unanimous in opinion that except urgent measures are taken by all humans, average global temperature rise would soon reach the deadly 2oC mark. When this happens, socio-economic livelihoods, particularly in developing economies, would be dealt lethal blow in the wake of associated natural causes such as increased disease burden, soil nutrient destruction, desertification, food insecurity, among others. To avert imminent dangers, nations, including those from Africa, signed a legally binding universally accepted climate control protocol to propagate and regulate environmentally-friendly behaviours globally. The climate vulnerability of Africa as established by literature is concerning. Despite contributing relatively less than other continents to aggregate environmental injustice, the continent is projected to bear the most brunt of environmental degradation. This is on account of her inability to put systems and mechanisms in place to stem consequences of climate change. Hence, our resolve to use a combination of scientific and artistic models to design a response system for tackling climate challenges in Africa. Our model formulation encompasses computational model and creative arts model for drawing attention to environmentally friendly behaviours and climate adaptation and mitigation strategies. In this work, we focus on rural Africa to share experience of climate change impact on agriculture – mainstay of rural African economy. We examine the carbon footprints of a rural community in Nigeria – the Adum-Aiona community – as case study and for industrial experience. The authors will provide operational data to substantiate claims of existential threats posed by greenhouse gas (GHG) generation on livelihoods of rural dwellers. The study will also design and test a Climate Change Response System (CCRS) that will enable people to adapt and reduce climate change impact. To achieve the research objective, the researchers will review literature, gather requirements, model the proposed system using Unified Modelling Language (UML), and test CCRS statically. We expect that the implementation of the proposed system will enable people mitigate the effects of, and adapt to, climate change-induced socio-economic realities. This is besides the fact that the empirical data provided by the study will help clear doubts about the real or perceived threats of climate change. Finally, the industrial experience and case study we share from Africa using model-driven engineering approach will scale up the repository of knowledge of both climate change research and model-driven engineering community.
Keywords:
agriculture, climate change, visual and creative arts model, model-driven engineering, response systemReferences
AKANDE V., 2016, Calabar Carnival 2016 to Explore Climate Change Again, http://thenationonlineng.net/calabar-carnival-2016-to-explore-climate-change-again (15.04.2016).
Google Scholar
BABATUNDE H.O., 2007, A Comprehensive Approach to Visual and Creative Arts, Agege, Lagos, HOB Designs Nig. Limited, p. 9.
Google Scholar
BARBIER G., CUCCHI V., HILL R.C.D., 2015, Model-driven engineering applied to crop modeling, in: Ecol. Informatics 26, p. 173-181.
Google Scholar
BELLPRAT et al., 2015, Unusual past dry and wet rainy seasons over Southern Africa and South America from a climate perspective, in: Weather and Climate Extremes 9, p. 36-46.
Google Scholar
BRAMBILLA M., FRATERNALI P., 2014. Large-scale Model-Driven Engineering of web user interaction: The WebML and WebRatio experience, in: Science of Computer Programming 89, p. 71-78.
Google Scholar
BRUNELIERE H. et al., 2014, MoDisco: A model driven reverse engineering framework, in: Information and Software Technology 56, p. 1012-1032.
Google Scholar
BUBECK A., MAIDEL B., LOPEZ F.G., 2014, Model driven engineering for the implementation of user roles in industrial service robot applications, in: Proc. Technology 15, p. 605-612.
Google Scholar
CALATAYUD et al., 2016, Can climate-driven change influence silicon assimilation by cereals and hence the distribution of lepidopteran stem borers in East Africa?, in: Agriculture, Ecosystems and Environment 224, p. 95-103.
Google Scholar
CALEGARI D., MOSSAKOWSKI T., SZASZ N., 2016, Heterogeneous verification in the context of model driven engineering, in: Science of Computer Programming p. 1-33.
Google Scholar
CALZADILLA A.,, ZHU T., REHDANZ K., EHDANZ, TOL R.S.J., RINGLER C., 2014, Climate change and agriculture: Impacts and adaptation options in South Africa, in: Water Resources and Economics 5, p. 24-48.
Google Scholar
CERVERA et al., 2015, On the usefulness and ease of use of a model-driven Method Engineering approach, in: Informat. Systems 50, p. 36-50.
Google Scholar
CHABRIDON S. et al., 2013, Building ubiquitous QoC-aware applications through model-driven software engineering. Science of Computer Programming 78, p. 1912-1929.
Google Scholar
CHIDIEBERE O., CHIRWA P.W., FRANCIS J., BABALOLA F.D., 2016, Assessing forest-based rural communities’ adaptive capacity and coping strategies for climate variability and change: The case of Vhembe district in South Africa, in: Environmental Development.
Google Scholar
CHINOWSKY P., SCHWEIKERT A., HAY-LES C., 2014, Potential Impact of Climate Change on Municipal Buildings in South Africa, in: Proc. Econ. and Finance 18, p. 456-464.
Google Scholar
CICCOZZI F., CICCHETTI A., SJODIN M., 2013, Round-trip support for extra-functional property management in model-driven engineering of embedded systems, in: Information and Software Technology 55, p. 1085-1100.
Google Scholar
CUADRADO J.S. et al., 2014, Applying model-driven engineering in small software enterprises, in: Science of Computer Programming 89, p. 176-198.
Google Scholar
CLARKE et al., 2016, Climatic changes and social transformations in the Near East and North Africa during the ‘long’ 4th millennium BC: A comparative study of environmental and archaeological evidence, in: Quaternary Science Reviews 136, p. 96-121.
Google Scholar
DAVIES et al., 2014, The CancerGrid experience: Metadata-based model-driven engineering for clinical trials, in: Science of Computer Programming 89, p. 126-143.
Google Scholar
DAVIES et al., 2015, Formal model-driven engineering of critical information systems, in: Science of Computer Programming 103, p. 88-113.
Google Scholar
FANT C., SCHLOSSER A., STRZEPEK K., 2016, The impact of climate change on wind and solar resources in southern Africa, in: Applied Energy 161, p. 556-564.
Google Scholar
GARCIA-MAGARINO G. PALACIOS-NAVARRO, 2016, A model-driven approach for constructing ambient assisted-living multi-agent systems customized for Parkinson patients, in: The Journal of Systems and Software 111, p. 34-48.
Google Scholar
GORTON I., 2011, Essential Software Architecture. Springer.
Google Scholar
GRACE et al., 2015, Linking climate change and health outcomes: Examining the relationship between temperature, precipitation and birth weight in Africa, in: Global Environmental Change 35, p. 125-137.
Google Scholar
GURUNULE D., NASHIPUDIMATH M., 2015, Analysis of Aspect Orientation and Model Driven Engineering for Code Generation, in: Procedia Computer Science 45, p. 852-861.
Google Scholar
HOST M., REGNELL B., WOHLIN C., 2000, Using students as subjects - a comparative study of students and professionals in lead-time impact assessment, in: Empirical Software Engineering 5(3), p. 201-214.
Google Scholar
HUTCHINSON J., WHITTLE J., ROUNCEFIELD M., 2014, Model-driven engineering practices in industry: Social, organizational and managerial factors that lead to success or failure, in: Science of Computer Programming 89, p. 144-161.
Google Scholar
JONES M.R., SINGELS A., RUANE A.C., 2015, Simulated impacts of climate change on water use and yield of irrigated sugarcane in South Africa, in: Agricultural Systems 139, p. 260-270.
Google Scholar
KAHSAY G.A, HANSEN L.G., 2016, The effect of climate change and adaptation policy on agricultural production in Eastern Africa, in: Ecological Economics 121, p. 54-64.
Google Scholar
KLAUSBRUCKER et. al, 2016, A policy review of synergies and trade-offs in South African climate change mitigation and air pollution control strategies, in: Environmental Science & Policy 57, p. 70-78.
Google Scholar
KUSANGAYAS. et al., 2014, Impacts of climate change on water resources in southern Africa: A review, in: Physics and Chemistry of the Earth 67/69, p. 47-54.
Google Scholar
LI et al., 2015, Hydrological projections under climate change in the near future by RegCM4 in Southern Africa using a large-scale hydrological model, in: Journal of Hydrology 528, p. 1-16.
Google Scholar
LIM S. et al., 2016, 50,000 years of vegetation and climate change in the southern Namib Desert, Pella, South Africa, in: Palaeogeography, Palaeoclimatology, Palaeoecology 451, p. 197-209.
Google Scholar
LUKMAN T. et al., 2013, Model-driven engineering of process control software – beyond device-centric abstractions, in: Control Engineering Practice 21, p. 1078-1096.
Google Scholar
LUTJEN M. et al., 2014, Model-driven logistics engineering – challenges of model and object transformation, in: Procedia Technology 15, p. 303-312. 15, p. 303-312.
Google Scholar
MARTINEZ-GARCIA et al., 2015, Working with the HL7 metamodel in a Model Driven Engineering context, in: Journal of Biomedical Informatics 57, p. 415-424.
Google Scholar
MOYO E.N., SHINGIRAI S., 2015, Southern Africa’s 2012-13 Violent Storms: Role of Climate Change, in: Procedia IUTAM 17, p. 69-78.
Google Scholar
NIELSEN J., LANDAUER T., 1993, A mathematical model of the finding of usability problems, in: Proceedings of ACM INTERCHI'93 Conference, p. 206-213.
Google Scholar
PANESAR-WALAWEGE R.K., SABETZAD-EH M., BRIAND L., 2013, Supporting the very-fication of compliance to safety standards via model-driven engineering: Approach, tool-support and empirical validation, in: Information and Software Technology 55, p. 836-864.
Google Scholar
PEREZ et al., 2015, How resilient are farming households and communities to a changing climate in Africa? A gender-based perspective, in: Global Environmental Change 34, p. 95-107.
Google Scholar
RALEIGH C., CHOI H.J., KNIVETON D., 2015, The devil is in the details: An investigation of the relationships between conflict, food price and climate across Africa, in: Global Environmental Change 32, p. 187-199.
Google Scholar
RIESENFELD R.F., HAIMES R., COHEN E., 2015, Initiating a CAD renaissance: Multidisciplinary analysis driven design Framework for a new generation of advanced computational design, engineering and manufacturing environments, in: Comput. Methods Appl. Mech. Engrg. 284, p. 1054-1072.
Google Scholar
RUNESON P., 2003, Using students as Experiment Subjects – An Analysis on Graduate and Freshmen Student Data, in: (ed.) Linkman S., 7th International Conference on Empirical Assessment & Evaluation in Software Engineering (EASE'03), p. 95-102.
Google Scholar
RUTLE A. et al., 2015, Model-Driven Software Engineering in Practice: a Content Analysis Software for Health Reform Agreements, in: Procedia Computer Science 63, p. 545-552.
Google Scholar
SCHROTH G. et al., 2016, Vulnerability to climate change of cocoa in West Africa: Patterns, opportunities and limits to adaptation, in: Science of the Total Environment 556, p. 231-241.
Google Scholar
SAURO J., KINDLUND E., 2005, A Method to Standardize Usability Metrics into a Single Score, in: Proceedings of ACM SIGCHI Conference on Human Factors in Computing Systems, ACM, p. 401-409.
Google Scholar
SEO S.N., 2014. Evaluation of the Agro-Ecological Zone methods for the study of climate change with micro farming decisions in sub-Saharan Africa, in: Europ. J. Agr. 52, p. 157-165.
Google Scholar
Da SILVA R., 2015, Model-driven engineering: A survey supported by the unified conceptual model, in: Computer Languages, Systems & Structures 43, p. 139-155.
Google Scholar
SIROHI N., PARASHAR A., 2013, Component Based System and Testing Techniques, in Advanced Research in Computer and Communication Engineering, 2(6), p. 33-42.
Google Scholar
STEYNOR et al., 2016, Co-exploratory climate risk workshops: Experiences from urban Africa, in: Climate Risk Management.
Google Scholar
SVAHNBERG M., AURUM A., WOHLIN C., 2008, Using students as Subjects - An Empirical Evaluation, in: Proc. 2nd International Symposium on Empirical Software Engineering and Management ACM, p. 288-290
Google Scholar
TURNER C.W., LEWIS J.R., NIELSEN J., 2006, Determining usability test sample size, in: (ed.) Karwowski W., International Encyclopaedia of Ergonomics and Human Factors, CRC Press, Boca Raton, p. 3084-3088.
Google Scholar
WAUTELET Y., KOLP M., 2016, Business and model-driven development of BDI multi-agent system, in: Neurocomputing 182, p. 304-321.
Google Scholar
WEBBER H., GAISER T., EWERT F., 2014, What role can crop models play in supporting climate change adaptation decisions to enhance food security in Sub-Saharan Africa?, in: Agricultural Systems 127, p. 161-177.
Google Scholar
WEHRMEISTER et al., 2014, Combining aspects and object-orientation in model-driven engineering for distributed industrial mechatronics systems, in: Mechatronics 24, p. 844-865.
Google Scholar
van WESENBEECK C.F.A., 2016, Localization and characterization of populations vulnerable to climate change: Two case studies in Sub-Saharan Africa, in: Appl. Geogr. 66, p. 81-91.
Google Scholar
WUNDSCH M. et al., 2016, Sea level and climate change at the southern Cape coast, South Africa, in: Palaeogeography, Palaeoclimatology, Palaeoecology 446, p. 295-307.
Google Scholar
YOUNG A.J. et al. 2016, Biodiversity and climate change: Risks to dwarf succulents in Southern Africa, in: J. of Ar. Env.129, p. 16-24.
Google Scholar
ZINYENGERE N., CRESPO O., HACHIGONTAS., 2013, Crop response to climate change in southern Africa, in: Global and Planetary Change 111, p. 118-126.
Google Scholar
Authors
Emmanuel OkewuCentre for Information Technology and Systems, University of Lagos, Lagos Nigeria
Authors
Sanjay MisraDepartment of Computer and Information Sciences, Covenant University, Ota, Nigeria; Atilim University, Ankara, Turkey Nigeria
Authors
Jonathan OkewuDepartment of Visual and Creative Arts, Federal University, Lafia Nigeria
Statistics
Abstract views: 19PDF downloads: 6
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
