Low Power IoT Electronics in Precision Irrigation

Routis, George; Roussaki, Ioanna

doi:10.1016/j.atech.2023.100310

Cited by 10 publications

(5 citation statements)

References 14 publications

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“…Effective disease detection and management strategies are crucial for mitigating crop losses and ensuring food security [160]. Advances in AI-powered IoT devices and predictive analytics have shown promise in early disease detection and prevention [121,147,161].…”

Section: Crop Disease Detection and Managementmentioning

confidence: 99%

“…Precision irrigation systems and AI algorithms offer potential solutions to optimize water usage and improve crop yield. However, inadequate water governance frameworks and competing water demands from urbanization, industry, and ecosystem services exacerbate challenges in agricultural water management [152,160].…”

Section: Water Management and Irrigation Efficiencymentioning

confidence: 99%

“…[179] employed the Arduino Portenta H7 board in their investigation of a smart sensor for energy-saving in IoT PA. Similarly, studies by [133,[180][181][182][183][184][185] utilized Raspberry Pi and [95,107,136,160,186,187] employed Arduino. The authors of [188] proposed SEPARATE, a tightly coupled IoT infrastructure for deploying AI algorithms in smart agriculture environments, leveraging edge computing to enhance efficiency and responsiveness.…”

Section: Computation Componentsmentioning

confidence: 99%

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IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities

Senoo,

Anggraini,

Kumi

et al. 2024

Electronics

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The global agricultural sector confronts significant obstacles such as population growth, climate change, and natural disasters, which negatively impact food production and pose a threat to food security. In response to these challenges, the integration of IoT and AI technologies emerges as a promising solution, facilitating data-driven decision-making, optimizing resource allocation, and enhancing monitoring and control systems in agricultural operations to address these challenges and promote sustainable farming practices. This study examines the intersection of IoT and AI in precision agriculture (PA), aiming to provide a comprehensive understanding of their combined impact and mutually reinforcing relationship. Employing a systematic literature review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines, we explore the synergies and transformative potential of integrating IoT and AI in agricultural systems. The review also aims to identify present trends, challenges, and opportunities in utilizing IoT and AI in agricultural systems. Diverse forms of agricultural practices are scrutinized to discern the applications of IoT and AI systems. Through a critical analysis of existing literature, this study contributes to a deeper understanding of how the integration of IoT and AI technologies can revolutionize PA, resulting in improved efficiency, sustainability, and productivity in the agricultural sector.

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Section: Crop Disease Detection and Managementmentioning

confidence: 99%

Section: Water Management and Irrigation Efficiencymentioning

confidence: 99%

Section: Computation Componentsmentioning

confidence: 99%

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IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities

Senoo,

Anggraini,

Kumi

et al. 2024

Electronics

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“…A proposed innovative smart IoT-based system based on microprocessors and a Single-Board Computer (BSC) for data logging using various sensors [50] can monitor soil moisture, air humidity, air temperature, and UV light, supporting precision irrigation of crops and enabling real-time exploitation of data for minimization of errors, as well as forecasting.…”

Section: Farm Scenery Layermentioning

confidence: 99%

Integrated Service Architecture to Promote the Circular Economy in Agriculture 4.0

Varella,

Oliveira Neto,

Stefani

et al. 2024

Sustainability

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Innovation has been the transforming tool of precision agriculture as a response to population growth and the demand for more food with quality, less waste, food security, and sustainable management of environmental resources. The challenges are to increase the productivity of cultivated areas, both for current and future areas, to manage the use of potable water, scarce in many regions, to keep the soil fertile, and to reduce waste through reuse, optimization, resource sharing, and operational and strategic management based on accurate information of planting, harvesting, and management of environmental conditions, which are also objectives of the Circular Economy. Therefore, using Industry 4.0 technologies in agriculture becomes fundamental to facing such challenges. This paper presents a systematic literature review on Industry 4.0 technologies adopted in agriculture for sustainable development, considering environmental, economic, and social benefits. The research pointed to the use of IoT in irrigation control systems by sending automatic commands, monitoring soil and weather conditions, in the use of machinery with some automation features and in cloud data storage systems, and with the use of Big Data analytical tools, with access by mobile devices, these uses contribute to operational and strategic decision making in the management of planting and harvesting. However, the literature review did not find a technological architecture for Integrated Services in Agriculture 4.0. Thus, this paper proposes a Service Architecture that enables the promotion of a Circular Economy in Agriculture 4.0. The contribution of this article to the theory is in the expansion of knowledge of the use of technologies in Agriculture 4.0. In terms of practice, this article provides an Integrated Service Architecture so that new products can be developed for Agriculture 4.0 and thus contribute to society in reducing food insecurity, generating environmental, economic, and social benefits, and promoting the Circular Economy in Agriculture 4.0.

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“…This system makes it possible to irrigate land according to environmental conditions that occur autonomously. Precision irrigation models in agriculture can be realized due to AI decisionmaking based on information from data from several IoT sensors [51], [52].…”

Section: B Farm Irrigationmentioning

confidence: 99%

A Review: Artificial Intelligence Related to Agricultural Equipment Integrated with the Internet of Things

Wildan

2023

JATM

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Abstract—The development of modern technology has brought progress to the agricultural sector. Previously, farming was carried out using traditional methods, resulting in lower crop production. Now the world is faced with various problems, there are challenges such as climate fluctuations and increasing human population. This problem causes food needs to increase drastically, so adopting Industry 4.0 technology in the agricultural sector is necessary. Artificial Intelligence (AI) and Internet of Things (IoT) are part of industrial technology advances 4.0 that can be applied to modern agriculture. This paper reviews several AI technologies used in the agricultural sector, such as Fuzzy Logic (FL), Artificial Neural Network (ANN), Machine Learning (ML), Deep Learning (DL), Genetic Algorithm (GA), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), and Decision Support System (DSS). The application form of integration between AI and IoT is divided into several categories: soil monitoring, agricultural irrigation, fertilizer spraying, pest and plant disease control, harvesting, forecasting, and yield monitoring. This review paper was created to provide a comprehensive overview of modern agriculture integrating AI and IoT. This form of application makes it possible to predict the future of agriculture so that it can manage resources more efficiently and run autonomously. This review aims to analyze and explore the latest developments in integrating AI and IoT in agricultural equipment in the period 2019 to 2023. Thus, it is hoped that this article can provide in-depth insight into future agricultural technology advances. Keywords—Artificial Intelligence (AI), Internet of Things (IoT), Agriculture, Integration of AI and IoT, Smart farming.

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Low Power IoT Electronics in Precision Irrigation

Cited by 10 publications

References 14 publications

IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities

IoT Solutions with Artificial Intelligence Technologies for Precision Agriculture: Definitions, Applications, Challenges, and Opportunities

Integrated Service Architecture to Promote the Circular Economy in Agriculture 4.0

A Review: Artificial Intelligence Related to Agricultural Equipment Integrated with the Internet of Things

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