India\'s vision for inclusive growth focuses on the importance of meeting affordable housing needs, especially in rural and semi-urban regions. The present study discusses cost-effective construction techniques using locally available sustainable materials and in conjunction with government programs like the Pradhan Mantri Awas Yojana (PMAY) and the Gharkul Yojana. Based on a 600 sq.ft. home in Rahuri village, Maharashtra, the study discusses the use of alternative materials such as fly ash bricks, bamboo, recycled steel, and ferrocement. The use of these locally available materials not only ensures environmental sustainability but also reduces the cost by as much as 35% over conventional construction techniques. The study involves comparative analysis of conventional and sustainable materials, accurate cost calculation, environmental assessment, and strategies towards the inclusion of necessary infrastructure. Synergizing with national housing policy and focusing on a strategy of community participation, the paper develops a replicable model that can be implemented in different regions, with a call for a paradigm shift in built practices towards sustainable built practices in order to achieve the vision of \'Housing for All\' in India.
Introduction
1. Overview
The project addresses the critical need for affordable housing in rural and semi-urban India, driven by rising land prices, urban migration, and economic disparity. It proposes a cost-effective, eco-friendly, and replicable housing model, focused on a 600 sq.ft. dwelling in Rahuri village.
2. Key Objectives
Design Low-Cost, Sustainable Homes using local materials like fly ash bricks, bamboo, recycled steel, and ferrocement.
Leverage Government Schemes such as PMAY and Gharkul Yojana to reduce financial burdens on low-income groups.
Ensure Climatic and Cultural Relevance through locally adapted designs.
Promote Community Engagement and job creation in the housing sector.
Enable Scalability and Replication for broader national implementation.
3. Problem Statement
India faces a housing shortage of over 19 million units, especially for EWS and LIG groups. Traditional materials and practices are costly and environmentally harmful. Awareness and access to government schemes are also limited. The project seeks to bridge this gap through cost-efficient, sustainable, and policy-integrated housing solutions.
4. Methodology
Policy Analysis: Evaluated PMAY and Gharkul Yojana for financing and eligibility.
Site Assessment: Studied Rahuri's climate, soil, labor, and materials.
Material Selection: Chose green materials to cut costs and environmental impact.
Cost & Sensitivity Analysis: Found ~34% savings using sustainable models over traditional ones.
Design and Structural Planning: Focused on energy efficiency, passive ventilation, and minimal infrastructure needs.
Financial Assessment: Calculated costs with/without subsidies to measure affordability.
Documentation: Compiled CAD layouts, comparative cost charts, and sustainability reports.
5. Cost Comparison
Category
Traditional
Sustainable
Savings
Total Cost
?5.46 lakh
?3.58 lakh
~34%
Rate/sq.ft.
?911
?598
Carbon Emissions
High
Low
Water & Energy Use
High
Low
Construction Time
8–12 weeks
4–6 weeks
Green materials not only reduce cost but also improve thermal comfort, reduce utility bills, and support local economies.
6. Results & Impact
Demonstrated Feasibility: Sustainable housing models can significantly reduce costs while improving living standards.
Better Health & Education Outcomes: Stable homes improve well-being, school performance, and reduce disease.
Social & Economic Benefits: Increased disposable income, reduced poverty, lower public expenses on homelessness.
Environmental Gains: Reduced embodied energy and improved climate resilience.
7. Case Studies (Selected Highlights)
Kerala Eco-Village (2020): 600 sq.ft. homes using bamboo and earth blocks at ?3.6 lakh; integrated rainwater harvesting.
Odisha Cyclone Relief (2020): Resilient ferrocement houses for ?3.7 lakh; quick deployment in disaster zones.
Latur MHADA Scheme (2017): Modular concrete units at ?4.1 lakh; high local employment.
Tamil Nadu Pilot (2018): 600 sq.ft. green homes using mud blocks at ?3.4 lakh; challenges with public acceptance addressed through awareness.
Conclusion
The Rahuri village, Maharashtra, affordable housing project proves that sustainable construction techniques can reduce cost and environmental footprint by half and raise the standard of living of low-income families. Using locally available, green materials like stabilized mud blocks (SMBs), fly ash bricks, bamboo, and ferrocement, the cost of building a 600 sq.ft. house was lowered by about 34% against traditional construction—?3.58 lakh versus ?5.46 lakh. Not only do these materials reduce embodied energy and greenhouse gas emissions, but they also increase thermal comfort, resulting in healthier living conditions. Integration with government initiatives like Pradhan Mantri Awas Yojana (PMAY) and Gharkul Yojna makes it even more cost-effective and affordable to economically weaker sections. The success of the project proves the applicability of sustainable materials, low-cost design, and policy intervention in solving India\'s housing shortage, providing a replicable model for rural and semi-urban towns across the country.
References
[1] Adeyemi, A. B., & Ohakawa, T. C. (2024). Affordable Housing Solutions: Real Estate Strategies for Addressing Urban Population Growth.
[2] Singh, D., Yadav, A., & Deb, A. (2024). A Review on Sustainable Affordable Housing in India. ShodhKosh: Journal of Visual and Performing Arts, 5(1).
[3] Lall, A. B., Sethi, G., & Subrahmanyam, N. (2023). Healthy Affordable Housing in India. Global Buildings Performance Network.
[4] Agarwal, S., Mandal, S. N., Bajaj, D., & Singh, T. P. (2021). Affordable Housing and its Sustainability – A Review of Critical Success Factors (CSFs).
[5] Gopalan, K., & Venkataraman, M. (2015). Affordable Housing: An Academic Perspective on Policy and Practice in India. IIMB Management Review, 27(2), 129- 140.
[6] Sengupta, U. (2006). New Frontiers and Challenges for Affordable Housing Provision in India. In Housing for the Urban Poor: Policy and Practice in Developing Countries (pp. 211- 230). Routledge.
[7] Monitor Deloitte. (2013). State of the low-income housing market: Encouraging progress & opportunity to realize dreams of millions. Mumbai.
[8] CREDAI. (2013). Assessing the economic contribution of India\'s real estate sector. New Delhi.
[9] Horner, H. (2009). Affordable housing research and recommendations. Minneapolis, MN: McKnight Foundation.
[10] High Level Task Force on Affordable Housing for All. (2008, December). Report of the High Level Task Force on Affordable Housing for All. New Delhi: Government of India.
[11] Kundu, N. (2003). The case of Kolkata, India. Understanding slums: Case studies for the global report on human settlements.
[12] Eggers, F., Kraus, S., Hughes, M., Laraway, S., and Snycerski, S. (2013). Implications of customer and entrepreneurial orientations for SME growth. Management decision, 51(3), 524-546.
https://www.emerald.com/insight/content/doi/10.1108/00251741311309643/full/html
[13] Ghatasheh, N. (2014). Business analytics using random forest trees for credit risk prediction: a comparison study. International Journal of Advanced Science and Technology, 72(2014), 19-30.
https://onlinelibrary.wiley.com/doi/abs/10.1111/caim.12224
[14] Griva, A., Bardaki, C., Pramatari, K., and Papakiriakopoulos, D. (2018). Retail business analytics: Customer visit segmentation using market basket data. Expert Systems with Applications, 100, 1-16.
https://www.sciencedirect.com/science/article/pii/S0957417418300356
[15] Gupta, S., Leszkiewicz, A., Kumar, V., Bijmolt, T., and Potapov, D. (2020). Digital analytics: Modeling for insights and new methods. Journal of Interactive Marketing, 51(1), 26-43.
https://journals.sagepub.com/doi/abs/10.1016/j.intmar.2020.04.003
[16] Hock-Doepgen, M., Clauss, T., Kraus, S., and Cheng, C. F. (2021). Knowledge management capabilities and organizational risk-taking for business model innovation in SMEs. Journal of business research, 130, 683-697.
https://www.sciencedirect.com/science/article/pii/S0148296319307659
[17] Kalema, B. M., and Carol, M. N. (2019). A statistical analysis of business intelligence acceptance by SMEs in the city of Tshwane, Republic of South Africa. Academy of Entrepreneurship Journal, 25(2).
https://www.academia.edu/download/87377070/A-statistical-analysis-of-business- intelligence-acceptanceby-smes-in-the-city-of-1528-2686-25-2-252.pdfWorld Journal of Advanced Research and Reviews, 2024, 24(03), 1567–1591 1590
[18] Liu, Y., Soroka, A., Han, L., Jian, J., and Tang, M. (2020). Cloud-based big data analytics for customer insight-driven design innovation in SMEs. International Journal of Information Management, 51, 102034.
https://www.sciencedirect.com/science/article/pii/S0268401219305183
[19] López-Robles, J. R., Otegi-Olaso, J. R., Gómez, I. P., and Cobo, M. J. (2019). 30 años de modelos de inteligencia en dirección y empresa: Revisión bibliométrica. International journal of information management, 48, 22-38.
https://www.sciencedirect.com/science/article/pii/S026840121730244X
[20] Mani, V., Delgado, C., Hazen, B. T., and Patel, P. (2017). Mitigating supply chain risk via sustainability using big data analytics: Evidence from the manufacturing supply chain. Sustainability, 9(4), 608. https://www.mdpi.com/2071-1050/9/4/608.