Agricultural Informatics

11 Chapter 12Figure 12.1 Architecture of sensor node.Figure 12.2 Side view of the designed agro farm structure for the Plane region.Figure 12.3 Full view of the designed agro farm structure for the Plane region.Figure 12.4 The structure of farm by applying suitable irrigation network of pip...Figure 12.5 Sensor interconnection through the Internet of Things.Figure 12.6 A flowchart which describes the complete operation of the proposed s...Figure 12.7 Placement of ultrasonic sensor with the Arduino to avoid the animal ...Figure 12.8 The probe connection of capacitive touch shield with Arduino to trig...Figure 12.9 Screenshot of the various sensors placed at the field site by consid...Figure 12.10 Dashboard snapshot of the sensor value in desktop.Figure 12.11 Dashboard snapshot of the sensor value in the android app.Figure 12.12 Hardware snapshot of proposed system under working condition.

1 Chapter 2 Table 2.1 Hardware for smart farming. Table 2.2 Technology of monitoring soil, climate and crop.Table 2.3 Technology of controlling pest.Table 2.4 Technology of using proper fertilizer.Table 2.5 Technology of monitoring intrusion.Table 2.6 Technology of monitoring weed.Table 2.7 Technology for water management.

2 Chapter 3Table 3.1 Depicted the available programs on Agro Informatics in few institutes.Table 3.2 Sample Program components of Agro Informatics.Table 3.3 Depicted the proposed UG, PG & research programs on Agriculture with A...Table 3.4 Depicted the proposed UG, PG & Research Programs on Computer Science w...Table 3.5 Depicted the proposed UG, PG & Research Programs on Computer Applicati...Table 3.6 Depicted the proposed UG, PG & Research Programs on Information Techno...

3 Chapter 4Table 4.1 Nature of devices in a drone.

4 Chapter 5Table 5.1 Review of different methods on IoT-based smart irrigation monitoring.Table 5.2 Details of communication protocols used with security vulnerabilities.Table 5.3 Details of sensors, micro-controllers and data storage used by differe...Table 5.4 Review of different IoT-based smart weather parameters monitoring.Table 5.5 Details of communication protocols used with security vulnerabilities.Table 5.6 Details of sensors, micro-controllers and data storage.Table 5.7 Review of different machine learning-based smart irrigation monitoring...Table 5.8 Details of communication protocols used with security vulnerabilities.Table 5.9 Details of sensors, micro-controllers and data storage.Table 5.10 Review of different machine learning-based smart weather monitoring.Table 5.11 Details of communication protocols used with security vulnerabilities...Table 5.12 Details of sensors, micro-controllers and data storage.Table 5.13 ML algorithms to handle security threats in IoT layered architecture.

5 Chapter 10Table 10.1 Comparison of user experiences of three types of small aircraft [3].Table 10.2 Different materials and its properties [20].Table 10.3 Details of open source FCUs [3].Table 10.4 Overall specific thrust of motor XM7015HD-11 (Source: http://www.dual...

6 Chapter 11Table 11.1 A survey analysis.

7 Chapter 12Table 12.1 Advantage of step farming in-plane region versus hilly region.Table 12.2 Water requirement (mm) of different crops.Table 12.3 The graph of packet count versus various links ID.

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Scrivener Publishing100 Cummings Center, Suite 541J Beverly, MA 01915-6106

Advances in Learning Analytics for Intelligent Cloud-IoT Systems

Series Editor: Dr. Souvik Pal and Dr. Dac-Nhuong Le

The role of adaptation, learning analytics, computational Intelligence, and data analytics in the field of cloud-IoT systems is becoming increasingly essential and intertwined. The capability of an intelligent system depends on various self-decision-making algorithms in IoT devices. IoT-based smart systems generate a large amount of data (big data) that cannot be processed by traditional data processing algorithms and applications. Hence, this book series involves different computational methods incorporated within the system with the help of analytics reasoning and sense-making in big data, which is centered in the cloud and IoT-enabled environments. The series publishes volumes that are empirical studies, theoretical and numerical analysis, and novel research findings.