A Virtual Soil Moisture Sensor for Smart Farming Using Deep Learning

Patrizi, Gabriele; Bartolini, Alessandro; Ciani, Lorenzo; Gallo, Vincenzo; Sommella, Paolo; Carratù, Marco

doi:10.1109/tim.2022.3196446

Cited by 40 publications

(14 citation statements)

References 42 publications

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“…The work outlined the construction of a low-cost and low-power wireless sensor network (WSN) based on photovoltaic (PV) sensor nodes that can obtain ambient circumstances and soil data [ 87 ]. Soil moisture sensors are the most critical installed sensors due to huge costs and difficulties in installation, reliability, and calibration.…”

Section: Resultsmentioning

confidence: 99%

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Adli

Remli

Wong

et al. 2023

Sensors

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As the most popular technologies of the 21st century, artificial intelligence (AI) and the internet of things (IoT) are the most effective paradigms that have played a vital role in transforming the agricultural industry during the pandemic. The convergence of AI and IoT has sparked a recent wave of interest in artificial intelligence of things (AIoT). An IoT system provides data flow to AI techniques for data integration and interpretation as well as for the performance of automatic image analysis and data prediction. The adoption of AIoT technology significantly transforms the traditional agriculture scenario by addressing numerous challenges, including pest management and post-harvest management issues. Although AIoT is an essential driving force for smart agriculture, there are still some barriers that must be overcome. In this paper, a systematic literature review of AIoT is presented to highlight the current progress, its applications, and its advantages. The AIoT concept, from smart devices in IoT systems to the adoption of AI techniques, is discussed. The increasing trend in article publication regarding to AIoT topics is presented based on a database search process. Lastly, the challenges to the adoption of AIoT technology in modern agriculture are also discussed.

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Section: Resultsmentioning

confidence: 99%

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Adli

Remli

Wong

et al. 2023

Sensors

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“…1 D). The sensors for the weather data collection were placed in close proximity to the agricultural bed [29] , [30] , [31] . The soil moisture sensors were approximately 10 cm long and were inserted 8 cm into the soil itself.…”

Section: Methodsmentioning

confidence: 99%

Enhancing agricultural automation through weather invariant soil parameter prediction using machine learning

Uttsha,

Haque,

Banna

et al. 2024

Heliyon

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“…An essential challenge addressed in this work was measuring soil humidity. In response, the study introduced a sophisticated soft sensing algorithm based on the DL algorithm, resulting in a virtual soil moisture sensor capable of overcoming the limitations of physical sensors and enhancing precision in soil moisture measurements [379].…”

Section: B Soil Moisture Monitoring Systemmentioning

confidence: 99%

Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey

Mowla,

Shah

et al. 2023

IEEE Access

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The increasing food scarcity necessitates sustainable agriculture achieved through automation to meet the growing demand. Integrating the Internet of Things (IoT) and Wireless Sensor Networks (WSNs) is crucial in enhancing food production across various agricultural domains, encompassing irrigation, soil moisture monitoring, fertilizer optimization and control, early-stage pest and crop disease management, and energy conservation. Wireless application protocols such as ZigBee, WiFi, SigFox, and LoRaWAN are commonly employed to collect real-time data for monitoring purposes. Embracing advanced technology is imperative to ensure efficient annual production. Therefore, this study emphasizes a comprehensive, futureoriented approach, delving into IoT-WSNs, wireless network protocols, and their applications in agriculture since 2019. It thoroughly discusses the overview of IoT and WSNs, encompassing their architectures and summarization of network protocols. Furthermore, the study addresses recent issues and challenges related to IoT-WSNs and proposes mitigation strategies. It provides clear recommendations for the future, emphasizing the integration of advanced technology aiming to contribute to the future development of smart agriculture systems. INDEX TERMSInternet of things, wireless sensor networks, wireless network protocols, smart agriculture applications.

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A Virtual Soil Moisture Sensor for Smart Farming Using Deep Learning

Cited by 40 publications

References 42 publications

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review

Enhancing agricultural automation through weather invariant soil parameter prediction using machine learning

Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey

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