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The study aims to develop recommendations for optimal Internet of things (IoT) based solutions for a smart precision irrigation automation platform using morphological thinking (MT). The smart irrigation system (SIS) can be applied for green roof and green wall (GRGW) design by studying the relationships and configurations that will be analyzed, listed and synthesized, representing “solutions spaces” and their possibilities.

The research examines studying various cases of SIS; and assessing and analyzing the identified case studies through a decision support system (DSS) considering several factors regarding IoT, plant characteristics, monitoring, irrigation system and schedule, climate, cost and sensors used.

To develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform.

The research paper analyzes and proposes a simultaneous solution to two conflicting problems. On the one hand, the paper proposes to apply greening of walls and roofs in hot arid regions, which will achieve greater environmental comfort. However, this is extremely difficult to implement in hot arid regions, since there is an objective problem – a lack of water. At the same time, the paper proposes the most rational approaches to organizing an irrigation system with the lowest water consumption and the highest efficiency for landscaping. Accordingly, this paper focuses on evaluating different types of SIS about the hot-arid climate in Qatar. The study aims to develop recommendations for optimal IoT-based solutions for a smart precision irrigation automation platform, which can be applied for green wall and roof design.

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 purpose of this paper is to assess the agricultural practices in a drought-prone region of India in an effort to find out how science, technology and innovation (STI) measures can address the existing problems and help achieve sustainable solutions. This study has been planned with two specific objectives: to study the agricultural practices of small and marginal-holding farmers in a drought-prone region and to examine the opportunities for suitable interventions to mitigate the impacts of droughts. The study is based on primary survey conducted in Banda district of Bundelkhand region, Uttar Pradesh, India.

Empirical survey was done in eight different blocks of a drought-prone region of India using structured questionnaire. The questionnaire was pre-tested with a group of 12 farmers during a workshop through a pilot survey conducted during April 2017. Stratified sampling based on land holdings (small farmers having 1–2 ha of land, medium farmers having 2.1–5 ha of land and large farmers having more than 5 ha of land) and irrigation types (canals and tube wells) were utilised in different blocks of the district for selecting farmers in the surveyed villages.

Findings suggest that due to various reasons like change in climatic conditions, frequent crop failure, crop diseases and high cost of production, farmers have adopted certain crops which are not suited to their agro-climatic conditions. The paper recommends that farmer’s school or “on-farm training school” have to be initiated to integrate farmers’ traditional knowledge with modern knowledge systems with amalgamation of STI tools.

Uttar Pradesh is divided into nine agro-climatic zones; however, this study is focused on Bundelkhand and may be region specific, though the findings are important for other drought-prone areas.

The paper links the existing agricultural practices and further linking them with farmers’ socio-economic, cultural and environmental settings. Only 17.5 per cent of respondents owned any agricultural equipment due to high cost of farm tools, difficulty in taking equipements on rental basis and lack of sharing tools among the farmers.

This paper targets small and marginal farmers in the drought-prone region of India who face the dual shock of climate impacts and poverty. Adoption of modern agricultural practices and use of technology is inadequate which is further hampered by ignorance of such practices, high costs and impracticality in the case of small land holdings.

This paper has advocated for well-organised, efficient and result-oriented STI system to mitigate the adverse impacts of drought-prone agriculture. Farming community in drough-prone areas needs adequate investment, local-specific technology, better quality inputs, real-time information on weather and most importantly latest know-how for sustaining commercial and cost effective sustainable agriculture.

This chapter presents the Smart Irrigation system using the Internet of Things (IoT). IoT Technology is a network of physical objects that are connected with sensors, software, etc. This chapter concludes the project based on the agriculture field that automates the irrigation process and on the agriculture field that automates the irrigation process and solves the challenge of water consumption in those areas. We have developed the system using different sensors like (1) Soil Moisture sensor, which measures the moisture present in the soil, (2) Humidity and Temperature Sensor (DHT11), which traces the temperature change. All these sensors are connected to the Node MCU ESP8266 microcontroller, which is also a Wi-Fi module. It uploads the data to the cloud and displays it in the form of readings detected by the Blynk Application. This sensor's reading values control the pump for emergency purposes, such as stopping the pump for irrigation. Thus, this project can automate the irrigation process by analyzing soil moisture and climatic conditions, covering essential aspects like less labor, power consumption, reliability, and cost.

The purpose of this paper aims to reduce the manpower, electricity, and water consumption for irrigation.

The IoT-based smart irrigation system designed with various sensors to collect farm field data, and stored all the data in the cloud for scheduling the irrigation.

This system reduces the water and electricity consumption, and labor cost.

Difficult to implement on a small farm field with different crops.

Crop type, soil type and environment data should be considered for better saving of water.

Reduces the water consumption, electricity, man power and increase production.

The soil type, crop type and environment data have been added before irrigation. The climate data also included before scheduling. Dynamic changing of irrigation timings based on the climate and sensor data.

The emerging technologies of the Fourth Industrial Revolution are transforming various industries, including agriculture. Unaware, young male and female farmers leave the agriculture profession as they perform unsustainable practices. Precision agriculture using the Internet of Things (IoT) is a solution to sustainable agriculture. Extension professionals are at the heart of disseminating agricultural advisory agricultural services in India. The discourse on the IoT is entering the space of extension advisory services (EASs) and social sciences. Thus, the present paper seeks to review the application of IoT in Indian agriculture, its challenges and its effect on EASs. The conceptual framework is drawn from disruptive and surveillance capitalist theories.

Online literature review was conducted on electronic e-book Ebsco, Google scholar, PubMed, Jane, j gate, research4life, springer journal and Mendeley databases for full-text repositories, textbook, thesis, web articles, newspaper articles, reports, blogs for the year 1990 to May 2021 using keywords “IoT application in agriculture,” “emerging technologies in agriculture,” “challenges in IoT application,” “extension advisory services sources of information,” “big data and extension advisory, “IoT and extension advisory in India.” Only publications in the English language were included.

IoT aids progressive farmers and small farmers alike. Drones, robotics, precision irrigation, livestock tracking and crop disease surveillance are examples of IoT applications in agriculture. Only large corporations and governments access IoT, and for them, big data storage is an issue. Privacy and security concerns demand upgrades in IoT systems. Solutions to the convergence of IoT with the cloud will leverage agricultural EASs, resulting in fast computing, precise and proactive up-to-date problem solving. Hence, the need for communication between firms and clients has ceased. Thus, the jobs of extension agents are replaced.

The competence of future human extension agents lies in reskilling as a “knowledge broker” of relationships and expertise, as s/he cannot have all multidisciplinary knowledge.

Although IoT applications in agriculture are available from a technological standpoint, there remains an awareness gap regarding the impact of IoT applications in agricultural EASs. This study will aid in a better comprehension of IoT applications from current and prospective EASs.

The Internet of Things (IoT) is becoming increasingly popular in agribusiness to help increase food production capacity for the ever-expanding global population. This chapter provides a holistic overview of the latest trends around the applications of IoT in agriculture. We begin by giving an overview of IoT and its capabilities, followed by a deep dive into the practical and realistic aspects of leveraging IoT into the agroecosystem. IoT is already being used for many intelligent agriculture applications, such as open-field agriculture, controlled environment agriculture (greenhouse), livestock breeding, agricultural machinery, and more. This chapter examines those applications and ventures beyond the farm into several other aspects of the ecosystem, including storage, warehouse ambiance control, agri-data analytics and decision control, logistics, environmental safety, etc. The contents of the chapter would be based on extensive studies and empirical analysis of the latest research papers on this subject from around the globe, accurately interpreted and transformed by the authors in light of their academic background and professional experience in the digital transformation arena.

This paper is a literature review on use of artificial intelligence (AI) among agricultural value chain (AVC) actors, and it brings out gaps in research in this area and provides directions for future research.

The authors systematically collected literature from several databases covering 25 years (1994–2020). They classified literature based on AVC actors present in different stages of AVC. The literature was analysed using Nvivo 12 (qualitative software) for descriptive and content analysis.

Fifty percent of the reviewed studies were empirical, and 35% were conceptual. The review showed that AI adoption in AVC could increase agriculture income, enhance competitiveness and reduce cost. Among the AVC stages, AI research related to agricultural processing and consumer sector was very low compared to input, production and quality testing. Most AVC actors widely used deep learning algorithm of artificial neural networks in various aspects such as water resource management, yield prediction, price/demand forecasting, energy efficiency, optimalization of fertilizer/pesticide usage, crop planning, personalized advisement and predicting consumer behaviour.

The authors have considered only AI in the AVC, AI use in any other sector and not related to value chain actors were not included in the study.

Earlier studies focussed on AI use in specific areas and actors in the AVC such as inputs, farming, processing, distribution and so on. There were no studies focussed on the entire AVC and the use of AI. This review has filled that literature gap.

The purpose of this paper is to present a new low‐cost system based on a spherical robot for performing moisture monitoring in precision agriculture.

The work arose from the necessity of providing farmers with alternative methods for crop monitoring. Thus, after analysing the main requirements, a spherical robot was chosen as a tentative approach. The presented work summarizes the work carried out in selecting the basics to apply in the robot, as well as its mechanical and electronic design. After designing and constructing the robot, several tests have been performed, in order to validate the robot for performing monitoring task and moving on different types of soil.

The performed tests reveal that spherical robot is a suitable solution for performing the task.

Some improvements in control should be applied in order to reach a fully autonomous navigation in very slippery soils. Nevertheless, the performance of the robot in teleoperated mode allows validating of the system.

The robot turned out to be friendly and harmless in its use for this application. The cost of final series will be affordable in comparison with the cost of other methods. Endurance of the robot can be considered as fair.

The paper presents a new tool for farming based on non‐common robot.

The present research expands the debate on environmental sustainability in the wine industry. Since the literature on sustainability and wine is relatively recent, current results do not cover all the practices that can be implemented along the wine supply chain. Thus, the paper presents a classification of environmental practices specific for the wine industry, according to the increased attention that has been paid to this topic in recent years. Moreover, it investigates the adoption level of these practices with reference to Italian wine producers.

The research presents a systematic literature review including papers published in academic journals during the past 30 years and in Italian specialised magazines. This methodology is useful to provide a clear overview of sustainable practices that can be adopted along the wine supply chain. Therefore, an empirical study based on the results of an online survey shows how wineries approach environmental sustainability.

The literature review provides a definition and classification of environmental practices in the wine industry, as well as identification of those that require further attention in the literature, suggesting future research paths. The results of the online survey give an overview of the adoption level of environmental practices and highlight widespread attention to all the listed environmental practices, including those not adopted.

From a theoretical point of view, this paper fills a literature gap in terms of the definition and classification of environmental practices that cover all wine supply chain processes, also providing a useful instrument for wine companies' managers. Moreover, the results of the empirical research give an overview of the adoption level of environmental practices in one of the most relevant countries in terms of wine production and highlight widespread attention to all the listed environmental practices, including those not adopted.