smart irrigation in tunnel farming using IOT

In a basic IOT system, different devices and services are connected to each other to establish a relationship and enhance themselves over the time being to perform complicated tasks.  Multiple interoperating components are needed to develop such kind of model. To define the components that show

Project Title

smart irrigation in tunnel farming using IOT

Project Area of Specialization

Internet of Things

Project Summary

In a basic IOT system, different devices and services are connected to each other to establish a relationship and enhance themselves over the time being to perform complicated tasks.  Multiple interoperating components are needed to develop such kind of model. To define the components that show the high level perspective of Internet of Things, needs a classification of components. (Buyya, Yeo, Venugopal, Broberg, & Brandic, 2009; Tilak, Abu-Ghazaleh, & Heinzelman, 2002; Tory & Moller, 2004) represents the specific classification of each component. Major components of this model are mentioned below:

• Hardware: consist of actuators, sensors, and embedded communication hardware.
• Middleware: “on demand storage and computing tools for data analytics”.
• Presentation: “easy to understand visualization and interpretation tools which can be widely accessed on different platforms and which can be designed for different applications”.
• To test the performance of the proposed system, two types of sensors (temperature, humidity and moisture sensors) were planted on a testing field.
• The input data received from the sensors is forwarded to the server and results are shown at an Android application and a web browser and in response a user can perform some actions.
• The three types of sensor data is received from two sensors and the calibrated output is processed using naïve bayes logic approach with the help of classification tables.

Project Objectives

• Approach specifically addresses irrigation issues of tunnel forming and can be efficiently used with either a sprinkling method or a drip irrigation method.
• Economical sensors are used, simple to reproduce the results.
• Trialed on limited field but can be applied for large size fields

•  Architectural stages of IoT

• The IOT Architecture generally comprises of these 4 stages stage1(sencer/Actuators)

• In the context of “Internet of Things” a thing, should be equipped with actuators and sensors thus giving the ability to accept, emit and process signals.

  stage2(Data Acquisition system)

• At this stage the collected data from sensors is in analogue form that needs to be converted into digital form for the aggregation and further processing. This stage performs the data aggregation and conversions functions on the collected data.

  stage3(Edge Analytics)

• Once collected sensor data has been converted into digital form and aggregated, now it requires further enhancement before it enters the big data warehouse, this is where Edge Analytics comes in.

  stage4(Cloud Anaytics)

• Data that needs deep processing gets forwarded to cloud-based systems or physical data centres.

Project Implementation Method

Followings are the major questions that the proposed study aims to address by implementing the IoT assisted in monitoring of the smart irrigation and application of the intelligent technologies to produce optimized recommendations.

• How to reduce the scarcity of sweet water reservoirs?
• How IoT can be used to calculate the smart irrigation by using weather parameters and other parameters in the field?
• Can statistical analytics be used in calculating smart irrigation in tunnel farming?

Is there any framework /model available in decision support system in smart irrigation?

IoT Architecture and Framwork

Generally, no researchers are agreed on proposed architectures of IOT. Different researchers’ proposed different architecture so there is no evidence of global agreement on that proposed architectures.

Three and Five layers Architeactures

Basic architecture that is proposed by most researchers is three-layer architecture (Mashal et al., 2015; Said & Masud, 2013; M. Wu, Lu, Ling, Sun, & Du, 2010). It’s the research of early stages in this field., these are three layers named as Perception, network and application layers.

Benefits of the Project

• The smart irrigation system for tunnel farming is an intelligent system that enjoys the benefits of the true decision making ability of the naive bayes approach.
• To test the performance of the proposed system, two types of sensors (temperature, humidity and moisture sensors) were planted on a testing field.
• The input data received from the sensors is forwarded to the server and results are shown at an Android application and a web browser and in response a user can perform some actions.
• The three types of sensor data is received from two sensors and the calibrated output is processed using naïve bayes logic approach with the help of classification tables.

• The proposed intelligent irrigation system for tunnel farming uses a set of sensors to collect data from soil moisture, air temperature and air humidity. The detail of these sensors is given below:

• The HL-69 hygrometer is used to detect the humidity of the soil. It provides better reading than other soil moisture sensors. Experts recommend this sensor for real-time monitoring of the soil moisture of plants in a tunnel farm and to build an automatic irrigation system. A typical HL-69 hygrometer

•  the few key features of the HL-69 Soil Hygrometer used for soil moisture sensing in a tunnel farm:

Technical Details of Final Deliverable

• The study discusses in this research was tested on a small area (such as small tunnel farms, home gardens, etc.) but the results of the experiments show that the used approach can be generalized and can be used for efficient irrigation of large size fields.

Other parameters of sensors can also be observed

The high tunnel farm has not typical size, but it should to be enormous enough for the cultivator to plant, monitor and gather the yield from inside the structure.

There is no standard size for a high tunnel, but it should be large enough for the grower to plant, monitor and harvest the crop from inside the structure. Tunnels are normally 12 to 24 feet wide, 8 to 12 feet tall at the middle (contingent upon width), and 36 to 72 feet in length, or a length in any four-foot interim.

A run of the mill moisture sensor regularly peruses measurement of 10–15 cm around the test. Be that as it may, the HL-69 hygrometer with long needles is adequate to cover territory of 2–3 feet in distance across. Here, the length of the sensor bar and number of sensors on the pole decides the territory of inclusion by a sensor.

A typical moisture sensor normally reads diameter of 10–15 cm around the probe. However, the HL-69 hygrometer with long needles is sufficient to cover area of 2–3 feet in diameter. Here, the length of the sensor rod and number of sensors on the rod determines the area of coverage by a sensor. The estimations by HL-69 hygrometer are ordinarily taken from 30 cm to 150 cm profound. To cover a region of 12 × 120 feet of a bamboo tunnel structure, 25 to 30 sensors are adequate. Likewise, two AM2302 sensors for every field are recommended for detecting temperature and humidity. A experiment was set up at the open air agribusiness lab at The Islamia University of Bahawalpur.  outside and interior perspective on the test-bed produced for the intelligent water system framework tests

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Agriculture

Core Technology

Internet of Things (IoT)

Other Technologies

Sustainable Development Goals

Quality Education, Clean Water and Sanitation

Required Resources

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