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From the perspective of any nation, rural areas generally present a comparable set of problems, such as a lack of proper healthcare, education, living conditions, wages and market opportunities. Some nations have created and developed the concept of smart villages during the previous few decades, which effectively addresses these issues. The landscape of traditional agriculture has been radically altered by digital agriculture, which has also had a positive economic impact on farmers and those who live in rural regions by ensuring an increase in agricultural production. We explored current issues in rural areas, and the consequences of smart village applications, and then illustrate our concept of smart village from recent examples of how emerging digital agriculture trends contribute to improving agricultural production in this chapter.

The United Nations (UN) adopted Sustainable Development Goals (SDGs); agenda 2030 focuses on Climate Action (goal 13), targeting climate adaptability, as well as resilience, awareness and improving policy mechanisms on climate change. In order to enhance climate adaptability, climate-smart agricultural practices (CSAP) is a necessary step. CSAP is a sustainable agriculture approach with a strong focus on climate dimensions. The three pillars of climate-smart agriculture (CSA) are ‘Adaptation’: adapting to climate change; ‘Resilience’: building resilience against it and ‘Remove’: reducing carbon emissions. The new world economy uses Industry 4.0 technologies for sustainable advancement, including blockchain technology, big data analytics, artificial intelligence (AI), augmented and virtual reality, industrial Internet of Things (IoT) and services. Hence, technology plays a significant role in climate sustainable agriculture practices. This chapter shall consider three technologies consisting of IoT, AI and blockchain technology which contribute to CSAP in pre-harvesting (monitoring climate as well as fertility status, soil testing, etc.), harvesting (tilling, fertilisation, seed operations, etc.) and post-harvesting (predicting weather factors, seed varieties, etc.) periods of agriculture. All these three technologies work like the human nervous system; IoT helps in converting various information regarding demography, climate change, local agricultural needs, etc. into world data; AI works like a brain in combination with IoT, helps predict the use of climate-smart technology and blockchain, the memory part of the nervous system which deals with supply-side and ensures traceability as well as transparency for consumers as well as farmers. Hence, this chapter shall contribute to the importance of these three technologies in adopting CSAP in three stages of agriculture.

The objectives of this paper are firstly to investigate the relationship between smart farming and sustainable development goal (SDG) 2 i.e. zero hunger. Secondly, the paper applies SWOT analysis to better understand the strengths, weaknesses, opportunities and threats of implementing smart farming in Southeast Asia (SEA). Finally, the paper provides research and practical implications for smart farming in SEA.

This study applies SWOT analysis to evaluate the strengths, weaknesses, opportunities and threats of smart farming in SEA in its goal to achieve zero hunger. The SWOT analysis is performed by conducting a comprehensive review of past and relevant literature on smart farming and its relationship with SDG 2. The use of SWOT analysis provides a foundation to identify the desired future position, identifies existing issues and better informs leaders and policymakers on how to resolve the weaknesses and take advantage of the opportunities available.

Smart farming has shown great promise in increasing food production sustainably whilst maintaining a high standard of food safety and quality. Smart farming offers a path towards achieving SDG 2 by providing innovative ways into a more profitable, resilient and green agri-food system. It is also found that a regional approach towards ensuring food security should be taken in SEA due to the dependency of the states on one another for the supply of food and agricultural products. For smart farming to take off in the region, a stronger government initiative is needed to encourage Science Technology Engineering and Mathematics (STEM) learning to equip the local workforce.

This study contributes to the literature by highlighting the role of smart farming in achieving zero hunger. This may assist policymakers to understand the implications of adopting smart farming in the region when compared to other competing trade locations. In addition, this study uses SWOT analysis to evaluate internal and external factors which may assist in formulating strategies by allowing researchers to gain insights and to think of possible solutions for existing or potential problems.

This paper seeks to identify the prevailing streams in the research of climate-smart agriculture in order to help to conceptualize this new scientific notion and assist in drawing clear borders between climate-smart agriculture, agricultural sustainability and resilience.

In order to conceptualize the climate-smart agriculture (CSA), the current research provides an in-depth bibliometric analysis indicating the prospective research directions in CSA. The findings of this paper are important in guiding the research on creation of climate-smart agriculture across different regions.

The notion of the CSA covers three main objectives: increased productivity, enhanced resilience and reduced environmental footprint of agriculture. It is found that due to its novelty, the climate-smart notion does not always have its defined research agenda and is considered to be both a constituent part of some other scientific framework (e.g. sustainability) and an independent research avenue.

This paper presents an in-depth analysis of the literature on the CSA. The linkages among the concepts, research centers and research strands are identified via the citation-based analysis.

Increasing trends of climatic risk pose challenges to the food security and livelihoods of smallholders in vulnerable regions, where farmers often face loss of the entire crop, pushing farmers (mostly men) out of agriculture in destitution, creating a situation of agricultural making agriculture highly feminization and compelling male farmers to out-migrate. Climate-smart agricultural practices (CSAPs) are promoted to cope with climatic risks. This study aims to assess how knowledge related to CSAPs, male out-migration, education and income contribute to the determinants of male out-migration and CSAPs adoption and how they respond to household food security.

Sex-disaggregated primary data were collected from adopter and non-adopter farm families. STATA 13.1 was used to perform principle component analysis to construct knowledge, yield and income indices.

Yield and income index of adopters was higher for men than women. The probability of out-migration reduced by 21% with adoption of CSAPs. An increase in female literacy by 1 unit reduces log of odds to migrate by 0.37. With every unit increase in knowledge index, increase in log-odds of CSAPs adoption was 1.57. Male:female knowledge gap was less among adopters. Non-adopters tended to reduce food consumption when faced with climatic risks significantly, and the probability of migration increased by 50% with a one-unit fall in the nutrition level, thus compelling women to work more in agriculture. Gender-equitable enhancement of CSAP knowledge is, therefore, key to safeguarding sustainable farming systems and improving livelihoods.

The enhancement of gender equitable knowledge on CSAPs is key to safeguard sustainable farming systems and improved livelihoods.

This study is based on the robust data sets of 100 each of male and female from 100 households (n = 200) using well-designed and validated survey instrument. From 10 randomly selected climate-smart villages in Samastipur and Vaishali districts of Bihar, India, together with focus group discussions, the primary data were collected by interviewing both men and women from the same household.

The purpose of this paper is to investigate the effects of climate smart agriculture knowledge transfers. As well as to examine the application of climate-smart agricultural (CSA) knowledge such as conservation agriculture, irrigation systems, integrated soil fertility management, bioenergy and agroforestry by smallholder farmers in Kenya.

The study applied comparative research methodology to compare climate smart agriculture knowledge application between smallholder participants in farmer field schools (FFS) and no FFS participation. This study used household data from 759 randomly selected rural agricultural households in three counties in Kenya. The study applied multivariate probit model to estimate CSA knowledge application by farmers who participated in field trainings and non-FFS participation farmers.

This study established that climate smart agriculture knowledge transfer through FFS increases farmers’ application of critical aspects of climate smart agriculture knowledge practices such as irrigation system, conservation agriculture and soil and water conservation. Such aspects have been noted as effective interventions against adverse climate change effects such as persistent droughts and flooding and soil infertility. Further findings illustrated that farmers who received CSA knowledge transfers applied agricultural insurance to mitigate rising climatic risks on their farms. Knowledge transfer interventions targeting affordability through subsidizing agricultural insurance are probable and more cost-effective measures that can be used to reduce smallholder farmers’ exposure to climate change-related risks.

This study provides information that was previously unknown about climate smart agriculture knowledge transfers and application among farmers who participated in field trainings and non-FFS participation farmers by using empirical data.

Reducing income gap and enhancing welfare of people can be achieved through improved performance regarding socio-economic indicators, which can support sustainable development. People living in villages tend to migrate to the cities with the hope of enhancing their income. People living in cities and income gap among the people in the cities are expected to increase further. Enhanced living conditions in villages can reduce the need for this migration and increase welfare of the people in the villages. This chapter aims to examine drivers for sustainable smart villages and ways for enhancing and supporting their effectiveness in socio-economic development, in enhancing welfare and living conditions of people living in villages, and in reducing income gap between urban and rural people. This chapter investigates potential and roles of sustainable and smart villages in enhancing welfare and living conditions of people living in villages. Furthermore, this chapter emphasises the villages’ roles in sustainable development as well as importance of transformation of villages into the sustainable and smart ones and establishment of sustainable and smart villages so that convergence, social inclusion and socio-economic indicators can be supported. This chapter explains drivers for transformation of the villages into the sustainable and smart ones as well as establishment of new sustainable and smart villages. This chapter provides recommendations for sustainable and smart villages effective in contributing to sustainable and socio-economic development. This chapter can be useful to urban planners, construction industry stakeholders, policy makers and researchers.

In this chapter, drone and vision camera technology have been combined for monitoring the crop product quality. Three vegetable crops such as tomato, cauliflower, and eggplant are considered for quality monitoring; hence, image datasets are collected for those vegetables only. The proposed method classified the vegetables into two classes as rotten and nonrotten products so the images were collected for rotten and nonrotten products. Three different features information such as chromatic features, contour features, and texture features have been extracted from the dataset and further used to train a Gaussian kernel support vector machine algorithm for identifying the product quality. The system utilized multiple features such as chromatic, contour, and texture features in classifier training which enhances the accuracy and robustness of the system. Chromatic features were utilized for detecting the crop while other features such as contour and texture features were utilized for further classifier building to identify the crop product quality. The performance of the system is evaluated based on the true positive rate, false discovery rate, positive predictive value, and accuracy. The proposed system identified good and bad products with a 97.9% of true positive rate, 2.43 % of false discovery rate, 97.73% positive predictive value, and 95.4% of accuracy. The achieved results concluded that the results are lucrative and the proposed system is efficient in agriculture product quality monitoring.

Information and communication technologies (ICT)-presented technological developments, such as soil sensors, remote sensing, artificial intelligence (AI) and big data, have shown the potential to increase crop output and quality while consuming fewer resources and having a smaller environmental impact. The first step in ushering in a new era of technological advancement in the agricultural sector in the Kingdom of Bahrain is evaluating how prepared farmers and farm owners are to adopt these technologies. Therefore, the current study examines how ICT are prepared, accepted and adopted in agriculture in the Kingdom of Bahrain.

The study's goals were attained by using both quantitative and qualitative methodologies. A survey was created to learn more about the present state of ICT usage in agriculture, including its awareness, readiness, acceptance and adoption. To strengthen the conclusions and investigate the current situation related agricultural behavior, production and the use of information technology (IT) to support agriculture in the chosen farms, four exploratory field visits were made. Additionally, a strength-weakness-opportunities-threat (SWOT)-threat, opportunities, weakness, strength (TOWS) analysis was performed to evaluate the Kingdom of Bahrain's readiness and long-term plans for implementing ICT in agriculture. On the basis of secondary data, survey data and interview findings, SWOT-TOWS were created.

The findings revealed insufficient knowledge and awareness about ICT in agriculture. Despite the high level of digital infrastructure readiness in Bahrain, farmers are not ready to adopt sophisticated devices and complex applications such as crop sensing tools, the internet of things (IoT) and AI; however, there is a strong acceptance among farmers to implement new ideas and agriculture approaches.

The Arabian Gulf Countries, which are characterized by an arid environment, sporadic vegetation, weak soil and a lack of water supplies and arable land, have few studies that explore the crucial role of ICT in growing the agricultural sector. Considering the influence of ICT on the provision of more productive agriculture in a challenging and complicated environment, the study contributes to the body of knowledge by conducting an empirical investigation that addresses an urgent issue. The study is considered one of the few in the countries of the Arabian Gulf to address this subject.

The consequences of extreme climatic events that threaten food security have created the urgent need to properly adopt climate-smart adaptation techniques to improve productivity. The study examined the sustainability responses to climate-smart adaptation and the implication it has for explaining the food security situations among farm households in the Central Region of Ghana.

We estimated Heckit treatment effect model to analyse cross-sectional data collected from randomly selected farmers in the Central Region.

Analysis of farm sustainability index suggests that farmers' agricultural practices in response to climate change are lowly or moderately sustainable. We further found that while majority of the farm households are severely food insecure or food insecure with hunger, only about one-third are food insecure without hunger and the remaining few being food secure. The sustainability of farm practices is being impacted by the farmers’ choice of climate smart adaptation measures at the farm level. Consequently, the farm households' food security situation is found to be improved when sustainable farming practices are employed in the face of managing climate change effects.

Conclusions drawn from the study findings give rooms for policy implications that suggest responsibilities for policymakers, farmers and other stakeholders to promote CSA practices in food crop production in Ghana. These policy implications will contribute to improve crop productivity, increase incomes and thus enhance food security among farm families. Awareness campaign about benefits of CSA practices and technologies need to be strengthened among farmers in Ghana by government and NGOs that matter in promoting farm resilience to climate change. Given the important impacts of sustainable farm practices on household food security situation, policies that seek to build the adaptive capacity of farmers to climate vulnerability impacts should take into consideration the sustainability dimensions of the adaptation and mitigation measures to be advocated for use at farm levels.

Our paper contributes to literature knowledge on climate-smart adaptation practices effect on food security as evidenced in some recent literature. The paper makes a unique contribution by highlighting the food security implication of the sustainability impact of CSA practices, thereby exploring sustainability as an impact pathway between climate smart adaptations practices and food security in a developing country like Ghana. We approached our study aiming at making new contribution by introducing in the study implementation a quasi-experimental research design which future studies on impacts of climate smart adaptation practices can replicate.