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Appropriate environmental circumstances are essential for supreme plant growth, improved yield, and resourceful consumption of water and diverse resources, and resourceful utilize of water and other assets. Automate the information attainment procedure of the soil situation and a variety of climatic parameter so as to overrun plant enlargement allow in sequence to be composed at high occurrence with fewer manual labour supplies. But maintain a greenhouse and its agricultural estate is tremendously the blue- collar and therefore the bulk of them achieve imperative operation instinctively. Also, agricultural researchers are facing a lack of high-quality data which is vital for crop growth. Thus we have studied the existing technologies and want to develop a automated greenhouse with gainful system for growing the crop to keep the system automate the greenhouse protection operation and observe the plant growth circumstances within the greenhouse personally from a remote location and send alert to the client if necessary.

Improper management of waste items generated by humans has been a persistent problem for a very long time. Proper disposal of waste generated in households, offices, hospitals,etc. is an essential part of waste management. Segregation of waste at the base level ensures proper disposal of different types of wastes. Initially, the widely used method for separating waste was through manual labour. This required a lot of manpower and time. Since then waste management technology has seen immense improvement. In this paper we have analyzed the existing studies based on automatic segregation of waste items. The main emphasis of our study is segregation done using computer vision, but a brief study on other methods of segregation such as sensor based and mechanical based separation has also been done in order to exhibit a comparison between them. The aim of this paper is to establish which method is the most efficient and outperforms others when it comes to efficient waste separation.

Farming is India's most important and fundamental occupation, meeting all of humanity's food needs. In recent years, due to increase in population, farming becomes important part of country’s economy. In present situation the use of IoT & ICT in farming is very limited, due to which many obstacles arise in the manual farming process. However, in today's digitised world, there is still manual labour in farming. Many challenges exist in traditional farming, such as lower productivity due to manual farming, high yield production costs, difficulty in predicting the crop to be grown, water irrigation problem, volatile weather conditions, incorrect fertiliser selection, difficulty in selecting a fertiliser for plant disease, and so on. The emerging technologies like IoT and machine leaning have a potential to solve such kind of problems in digitised way. So, these technologies can be used to address the above limitations with the concept of intelligent farming. The combination of IoT and Machine Learning would help farmers in making the production of organic crops of higher quality and good quantity than earlier. These technologies are having potential to reduce both labour and costs, improving crop production, making crops productive, and reducing the irrigation waste. The goal of this research paper is to suggest a system that have an integrated Machine learning and IoT solution which will be used to overcome the existing limitations of current farming practices along with many new opportunities. This research paper also discusses the different modules of proposed system along with the intended results.

Understanding the nature of rural landscape change during the urbanization process is vital to formulate rural management plans for sustainable development. However, there is little information on how rural landscapes changes and limited evidence as to how it can be improved. There were 244.9 million households in India of which 179.7 million households or 833 million people were in rural areas (SECC Survey 2011). Survey revealed that 87.2 million rural households reported one of more criteria of deprivation, while 92 million households were engaged in casual manual labour and agricultural activities. In agriculture, the role of women cannot be denied. They contribute in every operation of agricultural activities and are also active in allied sectors like cattle management, dairying, beekeeping, goat rearing mushroom production and poultry farming etc. Women participation in total workforce was assessed 27.44% as against 72.56% by male workforce in 2011. Share of women agricultural workforce in total workforce was computed to be 16.57% in 2001 which declined to 6.23% in 2011. Causes of decline may be their participation other sectors with improvement in their literacy rate which rose to 51.50% in 2011 as compared to 33.57% in 2001. The male-female sex ratio has registered a decline of 0.11% as compared to 2001 census. Women holding land account for only 13.31% as against 87.27% by men in Bihar. Share of women agricultural workforce in total agricultural workforce was estimated to be 19.32% as per census 2011. Analysis of CACP unit level data of Bihar for the year 2013-14, revealed that the contribution of women in agricultural activities was assessed to be 35.94%. Women’s contribution in agriculture is significant and plays diverse role, still their wages were found 7.04% less than their male counterparts during 2015-16. To strengthen women’s participation in agriculture and allied sectors and to improve their access to land, loan and other facilities, Ministry of Agriculture and Farmers Welfare has policy provisions like joint leasing for both domestic and agricultural land under National policy for farmers. Under credit facility provisions government has framed policy for issuing Kisan Credit Cards to women for creating livelihood through livestock practices and agricultural processing. Beside all efforts, there is still a wide gender gap in the state which may be addressed properly for overall development of women and enhancing the rural landscape of the state in particular and nation in general. The paper tries to analyze the role women in agricultural development of Bihar and the issues confronting them.

With the exponential advancements in technology each year, a plethora of applications have been developed ranging from the most basic to the most advanced use cases. The amelioration in the smartphone industry has proven to be a major factor in the rapid development of mobile applications. The time and cost required to build apps increases due to the presence of multiple platforms, resulting in different programming for each. Hence, to mitigate these challenges, the solution was found in hybrid applications. To join this race of the digital world, a cross-platform application was developed for college canteen, which administered the users to place orders efficiently through a mobile application. Concurrently, this expunged the canteen problem of crowd management by notifying the customers after order completion, and assisted the staff to become dexterous with the use of this technology, thereby reducing manual labour. This paper discusses the technologies used, comparative studies and results obtained after the development of the prototype of the proposed system.

The caste system – a system of elaborately stratified social hierarchy – distinguishes India from most other societies. Among the most distinctive factors of the caste system is the close link between castes and occupations, especially in rural India, with Dalits or Scheduled Castes (SC) clustered in occupations that were the least well paid and most degrading in terms of manual labour. Along with the Scheduled Tribes (STs), the SCs have the highest incidence of poverty in India, with poverty rates that are much higher than the rest of the population. Since independence, the Indian government has enacted affirmative action policies in educational institutions and public sector employment for SCs and STs. In addition, in the more populous states of India, political parties have emerged that are strongly pro-SC in their orientation in the more populous states of India. We use five rounds of all-India employment data from the National Sample Survey quinquennial surveys from 1983 to 2004 to assess whether these political and social changes has led to a weakening of the relationship between low caste status and occupational segregation that has existed historically in India. We find evidence that the occupational structure of the SC households is converging to that of the non-scheduled households. However, we do not find evidence of a similar occupational convergence for ST households.

This article aims to analyse the reasons for the intensive use of child labour in the 19 th century and its subsequent decline in the first third of the 20 th century in the context of an economy with a highly flexible labour supply like that of Catalonia. During the second half of the 19 th century, factors relating to family economies, such as numerous families and low wages for adults, along with the technologies of the time that required manual labour resources, would appear to explain the intensive use of child labour to the detriment of schooling. The technological changes that occurred during the first third of the 20 th century, the demographic transition and adult wage increase (for both men and women) explain the schooling of children up to the age of 15 and the consequent practical abolition of child labour in that new era of economic modernisation.