Internet of Things and Machine-Learning-Based Leaching Requirements Estimation for Saline Soils

Bashir, Rab Nawaz; Bajwa, Imran Sarwar; Shahid, Malik Muhammad Ali

doi:10.1109/jiot.2019.2954738

Cited by 36 publications

(14 citation statements)

References 39 publications

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“…The IoT technology is the evolutionary phase of the Internet that builds a global infrastructure uniting devices and people [46]. IoT has its origins in numerous previous technologies: ubiquitous information systems, sensor networks, and embedded computers.…”

Section: Internet Of Things (Iot)mentioning

confidence: 99%

Smart Irrigation for Climate Change Adaptation and Improved Food Security

Bwambale¹,

Abagale²,

Anornu³

2023

Irrigation and Drainage - Recent Advances

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The global consequences of climate change cannot be ignored. The agriculture industry, in particular, has been harmed, resulting in poor production as a result of floods and droughts. One in every three people in the world’s arid and semi-arid regions lacks access to healthy food and safe drinking water. Despite the fact that irrigation development is increasing in most developing nations, it still falls short of meeting current food demand, much alone predicted need by 2050. To feed the future population while combating climate change, agricultural practices must be precise. Scarce resources such as water, land, and energy will need to be exploited more efficiently in order to produce more with less. Smart irrigation is shaping up to bring answers to these twenty-first-century concerns. This chapter discusses improvements in smart irrigation monitoring and management systems that may be used to address climate, food, and population issues. It includes an overview of smart irrigation, smart irrigation monitoring, and smart irrigation management, as well as challenges and prospects related to climate change and food security. Smart irrigation may boost water savings and agricultural production, thereby improving food security.

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Section: Internet Of Things (Iot)mentioning

confidence: 99%

Smart Irrigation for Climate Change Adaptation and Improved Food Security

Bwambale¹,

Abagale²,

Anornu³

2023

Irrigation and Drainage - Recent Advances

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“…Soil salinity results in a reduction in the quantity and quality of agricultural items [8]. The major threat of soil salinity is the loss of precious land resources that become unfit for agricultural purposes [9]. The soil salinity distribution in the experiment area is shown in Fig.…”

Section: Figure 1 Factors Affecting Evapotranspiration (Et)mentioning

confidence: 99%

Context Aware Evapotranspiration (ETs) for Saline Soils Reclamation

et al. 2022

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Accurate Evapotranspiration for saline soils (ETs) is important as well as challenging for the reclamation of saline soils through an effective leaching process. Evapotranspiration (ET) by FAO-56 Penman-Monteith standard method is complex, especially for saline soils. Moreover, existing studies focus on the use of the Internet of Things (IoT) and machine learning-enabled smart and precision irrigation water recommendation systems along with the ET estimation by limited parameters. The ETs for saline soils are also equally important for the reclamation of saline soils, which is ignored by the existing literature. The study proposed IoT and machine leaching-based architecture of context-aware monthly ETs estimations for saline soil reclamation with the effective leaching process. The IoT-enabled crop field contexts in terms of crop field temperature, soil salinity, and irrigation water salinity are used as input features to the Long Short-Term Memory (LSTM) and ensembled LSTM models for monthly ETs predictions. The performance of the proposed solution is observed in terms of the accuracy of the machine learning models along with the comparison against the FAO-56 PM-based standard method. The implementation of the proposed solution reveals that the ensembled LSTM-based approach for ETs is more accurate as compared to the LSTM model with accuracies of 92 and 90% for the training and validation datasets, respectively. The predictions made by the ensembled LSTM are more in line with the FAO-56 PM-based method with a Pearson correlation of 0.916 as compared to LSTM models. The implementation of the proposed solution in real-time environments reveals that the proposed solution is more effective in reducing the soil salinity as compared to the traditional method.

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“…The different technologies used in IoT for farming physical structure, data acquisition, data processing, and data analytics, and compared various technologies like cloud computing, big data storage and data analytics with IoT are discussed in [50]. IoT and machine learning (ML) forms for are proposed for the salinity measurement of soil [51]. Photovoltaic Agricultural Internet of Things (PAIoT) is put forward in smart agriculture [52].…”

Section: Wireless Monitoring Systemmentioning

confidence: 99%

Intelligent Computing and Control Framework for Smart Automated System

Manikandan¹,

Ranganathan²,

Bindhu³

2022

Intelligent Automation &Amp; Soft Computing

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This paper presents development and analysis of different control strategies for smart automated system. The dynamic role of an electrical motor and sensor interfacing with wireless module becomes an essential element in a smart agriculture system to monitor various environmental parameters. The various key parameters such as temperature, humidity, air pressure, soil health and solar radiation are widely used to analyze the growth of plants and soil health based on different climate conditions. However, the smart development of an automatic system to measure these vital parameters provides a feasible approach and helps the farmers to monitor their crops productivity. In this paper, a smart sensor based intelligent and automatic control strategies such as fuzzy logic controller and PID (Proportional Integral Derivative) controller is developed to collect the real time environmental parameters and to adapt any environmental conditions by updating their membership functions automatically with the help of sensor outputs. This paper targets to bring the usage of sensor-based intelligent and automatic control methods in the field of an agriculture system which includes automatic solar panel tracking and control, environmental vital parameters measurement, monitoring and implementation of intelligent control methods. The different experiments have been carried out with the support of graphical and microcontroller programming environment. Experimental results provide that the proposed system effectively measure the environmental parameters and provide an accurate transmission of data for continuous monitoring. The advantage of the proposed system is simple, easy to implement and maintain the dynamic environment for plants with respect to any climate conditions.

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Internet of Things and Machine-Learning-Based Leaching Requirements Estimation for Saline Soils

Cited by 36 publications

References 39 publications

Smart Irrigation for Climate Change Adaptation and Improved Food Security

Smart Irrigation for Climate Change Adaptation and Improved Food Security

Context Aware Evapotranspiration (ETs) for Saline Soils Reclamation

Intelligent Computing and Control Framework for Smart Automated System

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