SMART CROP FIELD IRRIGATION IN IoT ARCHITECTURE USING SENSORS

Savitha, M.

doi:10.26483/ijarcs.v9i1.5348

Cited by 15 publications

(4 citation statements)

References 13 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…[100] also created an automated irrigation system using Arduino technology. Savitha and Maheshwari [101] also devised the concept of an automated and effective watering system by creating remote sensors with Arduino technology, which can boost the output by as much as 40%. Zimdahl [102] conducted extensive research on the subject and concluded that weeds were the greatest rivals for water, with plants starting to compete for water and nutrients when their roots overlapped in the soil.…”

Section: Automation and Robotics In Agriculturementioning

confidence: 99%

Seeding a Sustainable Future: Navigating the Digital Horizon of Smart Agriculture

Balyan,

Jangir,

Tripathi

et al. 2024

Sustainability

View full text Add to dashboard Cite

Agriculture is essential to the existence of the human race, as well as the foundation of our civilization, because it provides food, fuel, fiber, and other resources necessary for survival; however, it is facing critical challenges due to anthropogenic climate change, which hampers food and nutritional security. Consequently, the agriculture industry must adjust to farming issues, such as the shift in global temperatures and environmental degradation, the scarcity of farm workers, population growth, and dietary changes. Several measures have been implemented to enhance agricultural productivity, including plant breeding, genetic engineering, and precision agriculture. In recent years, the world has witnessed the burgeoning development of novel scientific innovations and technological advancements enabled by drones, smart sensors, robotics, and remote sensing, resulting in a plethora of revolutionary methods that can be applied to real-time crop modeling, high-throughput phenotyping, weather forecasting, yield prediction, fertilizer application, disease detection, market trading, farming practices, and other environmental practices vital to crop growth, yield, and quality. Furthermore, the rise in big data, advanced analytics, falling technology costs, faster internet connections, increased connectivity, and increases in computational power are all part of the current digitalization wave that has the potential to support commercial agriculture in achieving its goals of smart farming, resilience, productivity, and sustainability. These technologies enable efficient monitoring of crops, soil, and environmental conditions over large areas, providing farmers with data to support precise management that optimizes productivity and minimizes environmental impacts. Though smart farming has significant potential, challenges like high implementation costs, data security concerns, and inadequate digital literacy among farmers remain. In summary, agriculture is rapidly transforming from conventional to digital farming, offering global solutions, efficient resource utilization, and minimized input costs while fostering farmer livelihoods and economic growth. Delivering a comprehensive view of how technology could help in tackling critical issues like environmental degradation and threatened world biodiversity, this perspective emphasizes the perks of digitalization. Future advancements may involve data encryption, digital literacy, and particular economic policies.

show abstract

Section: Automation and Robotics In Agriculturementioning

confidence: 99%

Seeding a Sustainable Future: Navigating the Digital Horizon of Smart Agriculture

Balyan,

Jangir,

Tripathi

et al. 2024

Sustainability

View full text Add to dashboard Cite

show abstract

“…Jha et al [62] have also developed an automated irrigation system with Arduino technology to decrease human power and time consumption in the irrigation process. The concept of an effective and automated irrigation system was also created by Savitha and Uma Maheshwari [63] by developing remote sensors using Arduino's technology that can increase output by up to 40 percent. One of the many technologies used to measure the quality of soil moisture is used by soil moisture sensors.…”

Section: Irrigationmentioning

confidence: 99%

The Prospect of Artificial Intelligence (AI) in Precision Agriculture for Farming Systems Productivity in Sub-Tropical India: A Review

Naresh

Chandra

Vivek

et al. 2020

CJAST

View full text Add to dashboard Cite

Agriculture is becoming more integrated in the agro-food chain and the global market, while environmental, food safety and quality are also increasingly impacting on the sector. It is facing with new challenges to meet growing demands for food, to be internationally competitive and to produce agricultural products of high quality. To cope with these challenges, Agriculture requires a continuous and sustainable increase in productivity and efficiency on all levels of agricultural production, while resources like water, energy, fertilizers etc. need to be used carefully and efficiently in order to protect and maintain the soil quality and environment. Consequently, Agriculture needs help in handling the complexity, uncertainty and fuzziness inherent in this domain. It requires new solutions for all aspects of agricultural farming, including precision farming and optimized resource application. Artificial Intelligence (AI) technology helps various industries to improve production and productivity. In agriculture, AI also allows farmers to increase their productivity and reduce negative environmental impacts. AI is changing the way our food is processed, where emissions from the agricultural sector have decreased by 20%. Together with precision agriculture (PA) and other emerging technologies, artificial intelligence (AI) can play a key role in modernizing agricultural practices and achieving the goal of improving the productivity of alternative arable cropping systems. In offering progressive change with advanced approaches, AI's future in agriculture is well ahead. The aim of this paper is to review various agricultural intelligence applications and to reduce the use of colossal amounts of chemicals with the aid of these technologies, resulting in reduced spending, improved soil fertility and increased productivity. With AI tools and machine learning, farmers can improve yields, protect their crops and have a much more reliable source of food.

show abstract

“…"Monitoring contains modules like remainder, plant growth monitoring in various stages, irrigation planner, crop profit calculator, calamity check and problem identifier" (Mohanraj et al, 2016). According to the agricultural areas the prediction data varies and it is provided to the farmers so that they can plan for their farming (Savitha, UmaMaheshwari, 2018).…”

Section: Introductionmentioning

confidence: 99%

Smart farming in agricultural industry: Mobile technology perspective

Rađenović

Krstić

Marković

2020

Ekonomika poljoprivrede

View full text Add to dashboard Cite

The aim of this research is to examine key indicators that are necessary for the implementation and development of smart farming concepts in the agricultural industry, especially from the applied mobile technology point of view. Accordingly, the authors used a neural network based software solution to determine the correlation, relationship structure and partial contribution of indicators for the mobile technology development in agricultural industries in selected countries. The validity of the input-output model in a neural network based software solution was evaluated using the Minkowski error and Quasi-Newton method through several iterations/epochs. The neural network structure has shown the importance of particular indicators for adopting a mobile technology perspective in the agricultural industry, where the application of Information and Communications Technologies (ICT) in agriculture is most emphasized. Only those countries that invest the most in the ICT in the agricultural sector can achieve greater efficiency and productivity by applying smart farming.

show abstract

SMART CROP FIELD IRRIGATION IN IoT ARCHITECTURE USING SENSORS

Cited by 15 publications

References 13 publications

Seeding a Sustainable Future: Navigating the Digital Horizon of Smart Agriculture

Seeding a Sustainable Future: Navigating the Digital Horizon of Smart Agriculture

The Prospect of Artificial Intelligence (AI) in Precision Agriculture for Farming Systems Productivity in Sub-Tropical India: A Review

Smart farming in agricultural industry: Mobile technology perspective

Contact Info

Product

Resources

About