Publication Type : Conference Paper
Publisher : SpringerBriefs in Applied Sciences and Technology
Source : ICDSMLA 2019 [International Conference on Data Sciences, Machine Learning and Applications]
Campus : Amritapuri
School : School for Sustainable Futures
Center : Amrita Center for Wireless Networks and Applications (AmritaWNA)
Department : Mechanical, Sustainable Development
Year : 2020
Abstract : The soul of India lives in its villages. Indian villages are rich with varied cultures and professions. Pandori is one among them located in Kathua district of Jammu and Kashmir. One beautiful thing which makes Pandori stand apart from other villages is the talent of making different handicrafts, sweaters and other handmade items by women in the village. Women of the village were not able to generate income from their skills is lack of market due to which the idea of generating income was never an option for them. Skill development plays a major role in the development of the country. Due to lack of resources and support, major skills in Pandori are going in vain which if used properly plays a dominant role in the development of the village. Women of Pandori make beautiful handicrafts from plastic waste and helps in the reduction of plastic waste in the village, which in turn reduces the environmental effects of plastic waste in the village. If a small scale market is set up in the village it serves as a transporter of the goods made in the village to other places. This helps people to generate income and improve the standards of living and have a better life. When people of the village have better standards of living, it improves the condition of the village. Every little development in the village lays as a stepping stone for the development of our nation.
Cite this Research Publication : N. O. Teja, Srikar, T., G. Mahadev, V., Yaswanth, D., Renjith Mohan, and G, D. Sharma S., “Improving Income Generation Opportunities and Livelihood of Women in Pandori by Enhancing their Skills”, in ICDSMLA 2019 [International Conference on Data Sciences, Machine Learning and Applications], 2020 SpringerBriefs in Applied Sciences and Technology, 2019.