Background: Smart farming uses information and communication technology (ICT) to optimize crop and livestock environments. It is applied in greenhouses, vinyl houses, and livestock barns. By collecting data on crop growth and environmental conditions, smart farms create optimal growth environments. This leads to higher productivity and better quality with less labor, energy, and nutrient input than traditional farming methods. In Korea, crop production has declined due to fewer farmers, and over 80% of agricultural products are imported. The low birth rate and aging population are worsening the shortage of agricultural workers. It is predicted that Korea could face a food shortage in three years due to low self-sufficiency. Smart farms are seen as a solution. They can be implemented in urban areas and are considered a profitable model due to their high production potential. 
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Methods: Nutrient machines are a vital part of smart farming. They dilute and supply essential nutrients for crop growth. However, different machines require varying nutrient ratios, which complicates crop management. To address this, a recipe program has been developed. It automatically adjusts nutrient ratios according to the user&rsquo;s standard settings. This ensures uniform nutrient delivery, regardless of the type of machine used. 
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Result: The recipe program is expected to improve crop production. It ensures consistent nutrient supply, optimizing growth conditions. It also enhances user convenience by standardizing nutrient management across different machines, reducing complexity in crop cultivation.

A Study on the Standardization of Smart Farm Communication

<div>Background: Weather monitoring is an important aspect of crop cultivation for reducing economic loss while increasing productivity. Weather is the combination of current meteorological components, such as temperature, wind direction and speed, amount and kind of precipitation, sunshine hours and so on. The weather defines a time span ranging from a few hours to several days. The periodic or continuous surveillance or the analysis of the status of the atmosphere and the climate, including parameters such as temperature, moisture, wind velocity and barometric pressure, is known as weather monitoring. Because of the increased usage of the internet, weather monitoring has been upgraded to smart weather monitoring. The Internet of Things (IoT) is one of the new technology that can help with many precision farming operations. Smart weather monitoring is one of the precision agriculture technologies that use sensors to monitor correct weather. The main objective of the research is to design a smart weather monitoring and real-time alert system to overcome the issue of monitoring weather conditions in agricultural farms in order for farmers to make better decisions.&nbsp; 
 
Methods: Different sensors were used in this study to detect temperature and humidity, pressure, rain, light intensity, CO2 level, wind speed and direction in an agricultural farm and real time clock sensor was used to measured real time weather data. The major component of this system was an Arduino Uno microcontroller and the system ran according to a program written in the Arduino Uno software. 
 
Result: This is a low-cost smart weather monitoring system. This system&rsquo;s output unit were a liquid crystal display and a GSM900A module. The weather data was displayed on a liquid crystal display and the GSM900A module was used to send the data to a mobile phone. This smart weather station was used to monitor real-time weather conditions while sending weather information to the farmer&rsquo;s mobile phone, allowing him to make better decisions to increase yield.</div>

An IoT based Low-cost Weather Monitoring System for Smart Farming

Background: Women play a critical role in both household management and agricultural production in rural Bangladesh. In Dumuria Upazila, Khulna district, it is well known that women dairy farmers contribute significantly to household income and food security. However, they face socio-economic and gender-based barriers that affect their access to resources, decision-making power and adoption of modern technologies. This study explores gender roles, access to credit, ownership perception and the adoption of climate-smart agricultural practices among women dairy farmers, who spend their time mostly on the farming. 
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Methods: A qualitative interviewfor gender analysis was conducted among 133 women dairy farmers selected from a broader population of 3,050 women aged 20 to 89 years in Dumuria Upazila of Khulna district. The family income of those farmers comes mostly from dairy farming. Data were collected through 12 Key Informant Interviews (KIIs) and 3 Focus Group Discussions (FGDs) on demographics, household size, educational background, farming experience, access to credit, financial and decision-making involvement, asset perception and adoption of climate-smart technologies. The responses were analyzed to understand the gender dynamics and socio-economic conditions affecting the livelihood of those women. 
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Result: The higher number of the respondents (44 farmers, 33%) were aged between 30-49. Women managed both household and farming responsibilities, with family sizes ranged from 2 to 10 members and dairy farming experience ranging from new entrants to over 30 years. Educational attainment varied. Only 35 (26.31%) respondents had access to credit. Nevertheless, women showed increasing involvement in financial decisions and milk distribution. Although most assets were officially registered in their husbands&rsquo; names, 131 (98.50%) women perceived the assets as their own. Joint decision-making in income management was common, though in households with elders or in-laws decisions were largely elder-driven.Regarding climate-smart technologies, only 14 (10.5%) respondents acknowledged familiarity. Nine (6.77%) used biogas plants and two used biogas combined with vermi-composting. Other mentioned to include rubber mats, water pumps and fans-suggesting unintentional use of such technologies. However, 64 (48%) respondents were unaware, 53 (39.85%) marked &ldquo;N/A,&rdquo; and one responded negatively, highlighting a major awareness gap in climate-smart farming practices.It was concluded from the findings that while women in dairy farming are increasingly participating in financial and household decision-making, their formal financial empowerment, such as buying assets in their names or opening fixed deposit in bank and access to climate-smart technologies remain limited, with a significant awareness gap in sustainable farming practices underscoring the need for targeted education and support interventions. 
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Empowering Women in Dairy Farming: Gender Roles, Challenges and Climate Smart Practices in Southern Bangladesh

Background: In response to global challenges like increasing food demand, climate changeand resource scarcity, there is a critical need for innovative agricultural methods. This study centers on Smart Farming and Precision Agriculture, which integrate technologies such as the Internet of Things (IoT), artificial intelligence (AI), roboticsand data analytics. These technologies aim to optimize resource use, improve crop productivityand reduce environmental impact. Precision management, which involves tailoring farm inputs to specific field conditions, is central to this approach and is essential for promoting sustainable agriculture. 
 
Methods: This research was conducted over 2 years and 6 months at Amity University Uttar Pradesh, focusing on banana cultivation. The IoT-based system includes an Arduino UNO board, a SIM900 GSM module for data transmissionand a suite of sensors-soil moisture, temperature, humidity, PIR, NPK, pH and raindrop sensors. This configuration enables continuous monitoring and real-time data collection, allowing for informed decisions in farm management. Data is transmitted to a cloud-based platform for aggregation and analysis, enabling timely adjustments in irrigation, fertilizationand crop care based on real-time environmental and soil data. 
 
Result: The implementation of this smart farming system led to significant improvements in resource efficiency and crop monitoring. Water usage was reduced by approximately 25%, while fertilizer application decreased by around 30%, maintaining optimal soil pH levels of 5.5-6.5. These adjustments contributed to a 20% increase in crop yield over traditional methods. Remote monitoring allowed for prompt interventions, highlighting the system&rsquo;s potential for driving sustainable agriculture and addressing food demand challenges through IoT-driven solutions.

Enhancing Agricultural Efficiency Through Smart Farming and Internet of Things Enabled Precision Agriculture

Background: At the present time, various technologies have been used in the development of modern agriculture. The technology used to help in the development of agricultural farms is called a smart farm. Mashed Mushroom is a food due to their usefulness and high nutritional and good income, as this result, the researcher was interested in the use of technology and innovation of smart farms in the mashed mushroom cultivation house and find a mathematical model of the optimum temperature and humidity for growing mashed mushrooms. Furthermore, find a mathematical model of the yield amount of mashed mushrooms against temperature and humidity. 
 
Methods: There are 5 methods in this research, to be composed of studying the problem, planning the operation process, using technology and innovation in smart farms, collecting data and finally finding a mathematical model of the optimum temperature and humidity for growing mashed mushrooms. In addition, a mathematical model of the yield of mashed mushrooms was obtained.&nbsp; 
 
Result: The results showed that the mathematical model of the optimum temperature for mashed mushroom was T= 0.3267t3-2.83t2+7.1433t+20, the most appropriate temperature was 24.95&plusmn;5.557&deg;C at the average andthe mathematical model of the optimum humidity for mashed mushroom was H= -0.8417t3+4.82-0t2.1883t+59.65, the most appropriate humidity was 74.58&plusmn;15.451% at the average. In addition, the mathematical model of product yield of mashed mushrooms was&nbsp;<img alt="" src="data:image/png;base64,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" />= -1.479+0.055T+0.028H when temperature T and humidity H were determined.

Mathematical Model for Optimum Temperature and Humidity Determination of Mashed Mushroom in Greenhouses by using Smart Farm Technology and Innovation

<div>The rising global demand for food, coupled with the challenges of climate change, necessitates the adoption of advanced technologies to enhance agricultural productivity and sustainability. Precision agriculture, powered by innovative sensor technologies, is transforming farming by enabling real-time monitoring of crops, soil and environmental conditions. These sensors play a crucial role in optimizing resource utilization, improving yields and minimizing environmental impact. This paper explores key sensor technologies used in agriculture, including electrochemical sensors for plant health assessment, hyperspectral and multispectral sensors for crop analysis, infrared (IR) and LiDAR sensors for environmental mapping and soil moisture sensors for precision irrigation. Additionally, mechanical sensing technologies, temperature and humidity sensors (TMS) and biosensors, such as Surface Plasmon Resonance (SPR) sensors, are examined for their role in disease detection, food safety and environmental monitoring. Despite advancements in agricultural sensors, no single manuscript comprehensively lists all materials used in their fabrication. This paper highlights the critical role of materials, such as carbon nanotubes, graphene, metal oxides, conductive polymers and biocompatible composites, in improving sensor sensitivity, durability and efficiency that can be adapted for long-term agricultural applications. Furthermore, this review provides valuable insights into the role of advanced materials in agricultural sensor development, emphasizing the need for flexible, durable and highly sensitive plant sensors. This comprehensive analysis aims to guide researchers in developing next-generation agricultural sensors that enhance real-time monitoring, improve efficiency and promote sustainable farming practices.</div>

The Biophysics of Precision Agriculture: Smart Sensors and Materials for Sustainable Farming: A Review

Background: Smart Farming Technology (SFT) employs advanced tools and techniques to enhance agricultural productivity and quality. Despite its potential, the acceptance and understanding of SFT among farmers are influenced by factors such as geographical location, education level, income and awareness. This study focuses on small-scale farmers in Jangoan mandal, Telangana State, to explore their perspectives and practices concerning SFT. Given the digital technology gap in agriculture, this research is crucial for enhancing food availability, promoting rural development and providing valuable insights for policymaking. 
 
Methods: The study employed a descriptive analysis method, interviewing a sample of 252 out of 18,465 farmers using a semi-structured interview schedule. Spanning from 2022 to 2024. The interview schedule included semi-structured and structured questions to assess farmers&rsquo; knowledge, practices and understanding of SFT. The topics covered SFT techniques, awareness of SFT&rsquo;s benefits and challenges, sources of information and training and perceptions of SFT&rsquo;s impact. Data analysis was conducted using SPSS software to provide insights into SFT adoption among farmers. 
 
Result: Focusing on socio-economic and technological aspects. Results show that 79% of farmers believe SF reduces harvesting time and reliance on synthetic pesticides, while 72% assert that relevant regulations enhance biodiversity. Despite 82% recognizing the adverse effects of excessive chemical fertilizer use on soil and water quality and 80% willing to adopt alternative methods, only 6% report substantial annual incomes from agriculture. While 74% view SFT as strategic for crop management, many face storage and implementation challenges. This research highlights the need for comprehensive support from governments and agricultural institutions to bridge the digital technology gap, enhance food availability and promote sustainable agricultural development.

Assessing the Impact of Smart Farming Technology on Small-Scale Farmers: A Case Study of Jangoan Mandal, Telangana State

<div style="text-align:justify">Modern intensive monocropping system is becoming unproductive, pest ridden, loss incurring, and resource depleting and hence turning out to be untenable. Lack of discrimination in input use by farm managers and overall poor management are accelerating degradation and desertification processes, and loss of biodiversity particularly add in endangered regions. &nbsp;While, properly designed diverse and strategically located tree/seasonal crop based land use systems can contribute to ecologic services by mitigation land degradation, climate change and desertification, while conserving natural resources and biodiversity. Besides providing, diverse goods and services, on-farm diversity can be considered as an adoptive strategy in areas climatically and biologically vulnerable. Being a potential C sink, tree based land use systems can also mitigate negative impacts of CO2 emission. As green belt/bank these have an important role in maintaining air, water and soil quality in mining and industrial areas. The so-called cellulosic feedstocks can be grown on marginal land, enhance soil fertility by promoting the growth of various soil organisms, and provide a climate- friendly source of energy. There are plenty of underexploited but potential plant species which can find niche in the existing agroecosystems with substantial addition to total production while contributing sufficiently to ecological services. These needs to be identified and useful models are developed for specific situations.</div>

On-farm crop diversity for sustainability and resilience in farming - A review

<div style="text-align:justify">Background: Perception is the way something is regarded/understood. It is mainly created by two factors; one is physiological and another is psychological characteristics of the human being. Thus, perception is not only physiological process that is what one sees with the eyes it is a much more complex process involving psychological process too, by which any person selectively assimilates and gives meaning to the stimuli in the environment. It is subjective process, thatis why different people perceive the same stimuli in different manner. The current study aimed to study the factors affecting perception of farm families towards farming as an occupation. 
Methods: The present study was conducted to ascertain the factors affecting perception of farm families towards farming as an occupation. The results are based on the perspective of different researchers.&nbsp; 
Result: There were six major factorsidentified namely economic, socio-cultural, physical, personal, psychological and push and pull factors affecting perception. The economic factors comprised of variables like income, cost of agricultural production and vicious cycle of debt and loan in farming and socio-cultural factors had variables like professional and social status of farming along with family influence affecting children occupational choice. Personal factors consisted of personal interest and satisfaction of farmers derived from farming while physical factors included hard work and lack of resources along with hazardous working conditions in farming. Stress prevalentamong farmers and satisfaction of farmers either with farming income or its status and risk associated with farming as a profession were studied under psychological factors. Push and pull factors comprised the reasons of farm families attracting towards urban areas for achieving better employment avenues and higher social status and prestige associated with other occupations.</div>

Factors Affecting Perception of Farm Families Towards Farming as an Occupation

<div>Agriculture is the economic back-borne of majority of developing countries worldwide. The sector employs over 50% of the working population and contributes about 33% of the Gross Domestic Product (GDP) in majority of African states. However, such contribution by the agricultural sector is likely to be affected by climate change, increasing human population and urbanization which impact on available agricultural land in various ways. There is thus an urgent need for developing countries to create or adopt technologies such as; soil-less farming that will not only address climate change challenges but also enhance crop production for improved food security. This paper reviews the science, origin, dynamics and farming systems under the soil-less agriculture precisely hydroponic farming to assist in widening the scope of knowledge of the hydroponic technologies and their implementation in Africa.</div>