project mentor: dr. chitra babunathmara/ssnce_cb.pdf · water requirements of plants/crops and...

Sri Sivasubramaniya Nadar College of Engineering, India

SWARM: Sensor driven Water and Agricultural Resources Management

Final Report, CSIDC 2006

Project Mentor: Dr. Chitra Babu

Dept. of Computer Science and Engineering [[email protected]]

Team Members: Archana Ganesan Dept. of Computer Science and Engineering [[email protected]] Naren Athmaraman Dept. of Computer Science and Engineering [[email protected]] Rama Muthukumar Dept. of Information Technology [[email protected]] Srivathsan Soundararajan Dept. of Electrical and Electronics Engineering [[email protected]]

mailto:[email protected]

SWARM Final Report, CSIDC 2006 SSNCE

Abstract Efficiently managing the use of water and fertilizers has always been a major concern in

agricultural practices. The scarcity of fresh water has been one of the motivating factors in developing efficient irrigation systems. Apart from the environmental concern in water management, it facilitates better growth of the crops. The costs of over-irrigation includes additional water, higher fuel or electricity consumption, more pump maintenance, more labor, increased drainage and possibly salinity problems that can eventually lead to yield reduction. Under-irrigation reduces the yield and quality, and can lead to total crop loss. Hence automated irrigation systems can conserve water as well as aid proper growth.

Improper use of fertilizers can also affect the health of the crop. In low quantities, it can considerably retard crop growth and hence affect production. Synthetic fertilizers in high quantities pollute the soil and render ground water unsuitable for consumption. Measuring the nutrient availability in real time and properly delivering the right amount of the nutrients at the appropriate time can be immensely useful.

The primary objective of SWARM is to remotely monitor the water and nutrient availability and deliver the corresponding resources dynamically in accordance with the data collected. The system facilitates optimal use of water by synchronizing irrigation with current water requirements of plants/crops and automates water and nutrient delivery, thus helping in efficient management of large farms.

The SWARM system was implemented at a farm measuring 250 ft x 80 ft in Kuppam, Andhra Pradesh, India. Groundnut is being cultivated in the farm and hence the test case that we present deals with water and nutrient management in groundnuts. It was tested for a period of around one and a half months and results have been provided. The system has shown promising results when compared to manually supplying water and fertilizers. The SWARM software was written in the JAVATM programming language. Software Engineering methodologies were used in every stage of development of the SWARM system.

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1. SYSTEM OVERVIEW The SWARM system functions as an overall guidance system for the farmer. It integrates

both software and hardware components so as to completely automate the process of water and nutrient supply. The fundamental logic behind the system is real time, sectional monitoring and control. This ensures the delivery of the right amounts of water and nutrients at the right moment, thus ensuring that there is minimal wastage. The heart of the SWARM system is the SWARM Software. The SWARM software integrates the computer system with the sensors and the delivery system. Detailed description of the software and the hardware modules is presented in the forthcoming sections.

1.1. Scope, Constraints and Limitations

The SWARM system is intended for use in large agricultural farms and in places where precision farming is being practiced. The farm needs to be considerably large in order to enable sectional monitoring. The parameters that bring in these differences become significant only in case of large farms.

Availability of digital nutrient measuring sensors in India and to import it in the available time frame was one of the major constraints of the implementation of the SWARM project. Instead the nutrient measuring devices were replaced by digital, USB data out numeric keypads in order to manually feed in the available nutrient content values after periodic soil analysis tests. The implementation setup is otherwise completely non experimental.

The limitation of the SWARM System is that it can support only a maximum of one hundred and twenty seven devices. The number of devices supported under the USB standard brings in this limitation. Only one hundred and twenty seven devices can be polled, monitored and controlled by the system.

1.2. Design Methodology

The design phase of the system followed a bottom–up approach. The major modules comprising the system were identified as follows: 1.2.1 Data collection

Different crops were studied and their types, characteristics, and requirements have been documented for constructing the database. 1.2.2 Interface with sensors

The USB port routes the sensor input into the system. Each sensor inputs details about the moisture content and nutrient content in its section as bits. The data from each sensor is decoded and sent to the monitoring program periodically. A simulation of the above scenario has been developed. 1.2.3 Field Monitoring

The sensor input is compared to the values in the database. The SWARM software determines the need for nutrient and water supply to different sections, the percentage required and the time for which the corresponding valves have to be open. This information is sent to the delivery system. 1.2.4 Delivery System

The program sends appropriate signals to the parallel port of the system to initiate the delivery process. One valve controls the water flow while the other valve controls the flow of Urea Solution. Another ‘n’ valves are connected to pipes to distribute the required amount to the

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specific section, where ‘n’ is the number of sections in the farm. The valves are programmed to open for a specific time interval based on bit values written into the parallel port.

Different modules are implemented separately and are finally integrated. This approach has facilitated compartmentalization and easier design. Object oriented design methodology has been followed to ensure security and more structured access to information.

An iterative development approach has been adopted so that every step can be repeatedly scrutinized for improvement.

1.3. Novelty / Innovation

Computers are being used in agriculture in a big way these days. Their use has been restricted mainly to data entry and retrieval systems. They have been used to generate irrigation schedules, but not to actually irrigate the farm. The concept of software controlled, real time need dependant water and nutrient management is new to the field. Constantly monitoring the needs of the crops/plants by measuring the soil for the moisture content and nutrient availability can help us deliver the right amount so that wastage would be minimal.

2. SYSTEM IMPLEMENTATION AND ENGINEERING CONSIDERATIONS

This section discusses the implementation details and other considerations of the SWARM system. Section 2.1 presents the hardware aspects of the SWARM system. Section 2.2 elaborates on the SWARM software. Section 2.3 explains the overall working of the SWARM System. Section 2.4 presents the implementation issues and other engineering considerations associated with the system.

2.1. Hardware Aspects of SWARM

This section introduces the various hardware constituents of the system. The hardware consists of two parts – Sensor array system and the Valve delivery system. The sensor array system deals with acquiring outputs from the sensors that are deployed in the field and the valve delivery system is designed to control the opening and closing of the solenoid valves that are coupled mechanically with the container valves. The hardware operations are controlled by suitable programs and the communication between the hardware and the computer is effected through the parallel and the serial ports.

Figure 1: Hardware Block Diagram 2.1.1 Measurement of moisture and nutrient content

In order to obtain the inputs from the sensors, the computer decides which sensor to activate and sends the corresponding command signal through the parallel port. The appropriate

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sensor gets activated and the output from the sensor is read by the computer through the serial port. The software processes the information and decides on the level of irrigation and the quantity of fertilizers to be added. Hence, the values corresponding to the time duration for opening the valves are calculated and the outputs are continuously given and monitored by the low end programming. Moisture Meter Digital moisture meters are being used in the implementation of the project. The specifications of the device used is as follows,

Property Specifications Range 0-50% Output LCD display and USB data out Time between subsequent readings 5 seconds Cost INR 11,300 or USD 250 (approx) Country of Manufacture People’s Republic of China

Table 1: Moisture meter technical specifications* * data provided by local distributor M/S: Southern Scientific Instruments, Chennai, India.

This device was the most suitable moisture sensor for the SWARM system. SWARM needs a sensor that can be used for real time applications, one that can give instant readings whenever requested. This moisture meter is relatively inexpensive and is the most suitable for the purpose and hence is being used.

Measuring Nutrient Content

For this also a device that can provide instant readings is the one that is required. Though we could not buy this device due to lack of availability in India in this time frame and test our system with it, we make some suggestions on the device that is most suitable for the SWARM system. The Minolta SPAD-502 is the most suitable for our system. The Minolta SPAD-502 needs to be modified so that it gives USB data out. Technical specifications of this device are as follows,

Property Specifications Measurement Sample Crop leaves Measurement Area 2 x 3 mm Min. Interval Between Measurements Less than 2 seconds Accuracy With in +/-1.0 SPAD unit (at room conditions,

SPAD value between 0 and 50) Weight 225g not including batteries

Table 2: Minolta SPAD-502 technical specifications The SPAD count is used as the parameter for measuring or identifying whether the crop

needs nutrient supply or not. The chlorophyll present in the plant is closely related to the nutritional condition of the plant. For a particular plant species, a higher SPAD value indicates a healthier plant.

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2.1.2 Delivery Controller Hardware design deals with the selection of appropriate components and the suitable

voltage levels for the stated purpose. The operation of the relay in the valve controller circuit requires a dc input of 12V. In order to obtain this, the following power circuit was employed. The AC input from the supply is leveled by a 9-0-9 V 500mA step down transformer which is then fed to a diode rectifier. The output from the transformer is fed to a regulator and the dc output of 12V is taken across the capacitor ends. The capacitance C1 is designed to be 100micro farads and the resistance of R1 to be 1KΩ.

Figure 2: Delivery valve actuator circuit

The output pins of the LPT parallel port, namely D0-D7, i.e. pins 2-9 each are separately connected to the base of a BC 547 transistor. This transistor gives output when a high appears on the corresponding parallel port output pin. This output activates a relay which supplies 230V to the solenoid valve. The solenoid valve opens when 230V is supplied and closes when the supply is cut off. Hence the software will write the correct bit combination at the correct time to open and close each of the valves.

Figure 3: A six section delivery controller

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2.2 The SWARM Software

The software forms the core of the entire SWARM system. It is responsible for the monitoring and control of all events related to the cultivation of crops. It forms the interface between the sensors and the mechanical system that is used to deliver the nutrients/water. Each node independently handles the response to the sensor inputs that it deals with. The software can be divided into modules depending upon the phase of the activity. For instance, the entire process can be split into the pre – crop selection phase and post – crop selection phase.

2.2.1 Pre – crop selection phase

In the pre – crop selection phase, the software assumes the role of an assistant, helping the farmer decide the most suitable crop for conditions that are particular to a section. The farmer first selects a scanned image of the layout of his farm land. The software then processes this image and detects the boundary of the farm. It prompts the farmer to enter the dimensions of each of the edges of the boundary by displaying a graphically generated image. Then the farmer is prompted to enter the location descriptors of the farm, namely latitude and longitude information. This data is transmitted through the internet to the central agricultural help center of that district. This center fetches a remote sensing satellite image of the location and sends it back to the SWARM software. The SWARM software then processes this image to identify the variations in the land surface. This data along with other information obtained from the farmer such as soil compaction values, soil type and initial nutrient availability is taken into consideration. These details provide values for various parameters which are used in the computation of expected profits. The parameters are given different weights depending upon the degree of influence over the health of the crops. The software then uses a statistical model to compute the expected profits from the various parameters involved for different crops. The maximum profit is then computed and the most suitable alternatives are also provided to the farmer. The farmer then can choose the most suitable crop with due consideration of factors like demand for that crop, the availability of seeds, appropriate fertilizers, the expertise of the labor etc.

2.2.2 Post- crop selection phase

After the farmer chooses the crop to be cultivated the control is transferred to the software. The level of interaction required with the farmer is kept to bare minimum. Once the crop is selected, and the date of plantation is confirmed, the timers are set. The post – crop selection phase can be further divided into the Initialization phase and the Monitoring Phase.

2.2.3 Initialization

In the initialization phase the sensor inputs are not taken into consideration. The time period of the initialization phase is dependant on the type of the crop. The interaction is only between the software and the mechanical delivery system. The goal of this phase is to provide water and nutrients that are essential in the initial stages. A database is maintained that stores the details for various crops including information about the amount and time of requirements of water/nutrients after the crop is planted. This database is queried to retrieve information particular to that crop variety. Timers are initialized with values retrieved, in order to provide a callback after the time expires.

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Figure 4: Crop selection screen

A signal is generated at the stipulated time intervals. The software detects the signal and identifies the operation to be performed. Then the software signals the delivery controller as well as the solenoid valves that control the flow of water and fertilizers to the sprinkler. The cross-section of the solenoid valve is taken into account to calculate the amount of time the valve needs to open to supply the required amount of water. A signal is sent to the solenoid valve after the calculated time interval in order to stop the supply. In this phase, the supply of fertilizer/water is entirely dependant on the values in the database. Once the initialization phase is over, the monitoring phase begins.

Figure 5: Providing crop specific details

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2.2.4 Monitoring Phase

In this phase, the values from the sensors are detected and acted upon. The sensor output is forwarded to a hub which in turn is connected to a node. At each node, the software queries a database and checks whether the value is below the threshold for the existing stage and condition of the crop. If it is determined that the difference is not negligible, a signal is sent to the delivery controller as well as the solenoid valves. The software handles the delivery in the same manner as the supply of water/nutrients in the initialization phase. In case that the difference is deemed negligible, the value is simply ignored. This phase does not require any manual intervention. A detailed report of the various delivery activities are provided to the farmer.

Figure 6: Status report

The time and date of last supply, amount of supply of water and nutrients are provided in

a table format for the farmer. A predictive schedule of measurement of requirements as well as the delivery is provided for information. Typically at the end of this phase, the crop is ready for harvest. 2.2.5 Features

• The databases used in both the phases are constantly updated. This updation can be

performed both internally as well as externally. The software appends on to the existing database as and when it is being used. The data from external sources can also be added on. This makes it easy to provide free updates to the farmers that helps refine the granularity at which the software works.

• The software also maintains a provision to manually stop a particular signal from being sent to the delivery system. For instance, if there is a forecast of rain in a few hours, the farmer has the option to delay/cancel the watering of crops.

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• Apart from provision of periodical reports to the farmer, the requirements and supply are

stored in a database to provide backups in case of node failures. These are transferred to the back up nodes at specified time intervals, in order for the system to resume operation quickly.

2.3 Fault Tolerance in SWARM

The SWARM system is centrally controlled. In order to overcome the disadvantages of centralized control and to provide fault tolerance, multiple computer systems can be used Minimum number of computer systems for a relatively small farm is 2. In the case of large farms, the number of systems correspondingly increases such that each node is provided with a backup node.

Figure 7: POLL/ACK signal exchange

All the ‘n’ computer systems at a single farm are part of a local network. Each node

periodically polls its backup node, as well as the node for which serves as backup. If the node is active it responds with an acknowledgement signal. If a node does not receive an ACK signal within a time bound, it resends the POLL signal. Upon three consecutive time outs, the node is determined to be inactive.

Figure 8: Detecting node failures

If the given node is the backup, it takes over the workload of the failed node. No

computer in the system will be loaded to its theoretical maximum of 256 sections. Hence the takeover as the central controller is made feasible. Moreover, secondary connections are made from the backup node to the solenoid valves of the main node to facilitate the take over.

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Figure 9: Case when node‘d’ fails

If the failed node is a backup, then it becomes essential to search for a new backup. This

is achieved by sending a BCK REQ Signal. For instance, consider 5 nodes a,b,c,d.,e If d fails, e takes over the control. Node c looks for an alternate backup and send a BCK REQ signal to node a. If node ‘a’ is free, it responds with a BCK ACK signal else it sends the address of ‘e’ and the process is repeated.

If a node has received a poll request from a certain node within a particular time frame then it does not send a poll request to the same node for a certain time period. This is to avoid redundant polling checks. For instance, if a node ‘a’ has been polled by node ‘b’ and ‘a’ has sent an acknowledgement, then ‘a’ avoids polling ‘b’ for the next ‘n’ seconds.

Hence the reliability of the SWARM system is high and that is achieved without actually distributing control.

2.4. Functional Overview The software in the pre-crop selection stage helps the farmer in choosing the most profitable option for his farm. The farmer first selects a scanned image of the layout of his farm land. The software then processes this image and detects the boundary of the farm. It prompts the farmer to enter the dimensions of each of the edges of the boundary by displaying a graphically generated image. Then the farmer is prompted to enter the location descriptors of the farm, namely latitude and longitude information. This data is transmitted through the internet to the central agricultural help center of that district. This center fetches a remote sensing satellite image of the location and sends it back to the SWARM software. The SWARM software then processes this image to identify the variations in the land surface. This data along with other information obtained from the farmer such as soil compaction values, soil type, initial nutrient availability are taken into consideration. This data is used to divide the farm into sections that have independent requirements and is used to provide suggestions for the most profitable crop

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Figure 10: Fetching the satellite image

mix. The software then presents graphically with dimensions the best position for placing the sensors and the sprinkler valves. The farmer then follows the guidelines and instructions specified to install the sensors and the water and nutrient delivery system. Once the farmer decides on the date of sowing and reports it to the SWARM software it generates the pre sowing irrigation schedule and delivers the required amount of water. Once the seeds have been sown the sensors will the activated and periodically water content and SPAD value will be read from the respective sensors. This value is compared with the values in the database and the necessary action will be taken. 2.5 Implementation scenario and Issues

The system has been implemented in a small scale and tested for performance. A farm cultivating peanuts in Kuppam, Andhra Pradesh, India is our test site. Kuppam district is one of the very few places in India where precision farming is being practiced. The SWARM system is a combination of both hardware and software. Agriculture being one of the most practiced professions in developing nations, cost has been one of the major factor in designing the system. Hence the software is being loaded with most of the functionality. We plan to distribute the software free of cost as a service to humanity. Most of the farmers in India have not had formal education. This has been the motivating factor in maintaining the complexity of the system to the bare minimum. This just means that, the farmer or the user of this system will see a simple interface while all the complex functionalities are internal and are hidden from the farmer.

2.5.1 Implementation specific hardware requirements

This section specifies additional hardware that is needed for implementing the SWARM system. These can be bought directly from irrigation/landscaping equipment suppliers. The requirements are as follows,

Name Specifications/Remarks Quantity required Solenoid Valve 1 inch diameter N*+3 200 liter tank For mixing water and fertilizer, 2

inlets and 1 outlet 1

Large water tank # For storing water 1 PVC Pipe For distribution, 1 inch diameter As per requirement 0.5 HP motor driven pump

To provide the force for the water jet, so that it covers the entire section.

As per requirement

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USB Hub 16:1 connected as a daisy chain or custom made larger ones.

As per guidelines offered by the SWARM software, dependant on the number of sections.

Super enameled copper wire

To power the devices. As per requirement

* the number of sections in the farm, in our test case N=2. # in our implementation the village community water tank was used instead.

Table 3: Other hardware requirements 2.5.2 Prototype Implementation Process The SWARM system has been implemented in part. All new ideas have been tested and implemented, while trivial, off the shelf components have not been used, if they are not easily available in India or if they are too expensive. This section describes the implementation that we did in our test site.

The test site measures 250 ft X 80 ft and is rectangular in shape. The scanned jpeg image of the layout was fed into the system. The SWARM software analyses the .jpg image and detects the boundary of the farm. It then graphically displays the outline of the farm to the farmer. The farmer then keys in the dimensions of each of the edges of the farm as prompted to, by the software. The software then prompts the farmer to enter the latitude and longitude positional coordinates of his farm land. This is then sent to the server located at the central agricultural help centre. In our case the server is just another computer that reads this data being sent from the SWARM node and fetches the satellite image corresponding to that latitude and longitudinal positions. As we could not obtain satellite images, we took a sample image that has similar data. This data is identified by the software. The slope variations in the soil and soil compaction values are interpreted from the sample image. These parameters along with the identified boundary of the farm land are taken into consideration and are used to divide the farm in to sections. Our farm was divided into 2 such sections. The SWARM software also tells you where to place the sprinklers and the moisture meters.

Figure 11: Devices connected to the USB Hub

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Figure 12: Delivery System

A 200 liter tank was used as the mixing tank and the water inlet of this mixing tank was

connected with the community water supply tank. It is a 50,000 liter tank placed at a height of 40 feet. This inlet has a solenoid valve which regulates the water input. This inlet is hence computer controlled. A smaller tank that holds a 5% solution of urea is the second inlet to the mixing tank, refer Figure 12. This again is computer controlled. The moisture value measured by the moisture meter is read through the USB port.

Figure 13: The SWARM Control Room, note the delivery controller and the USB hub to

which the devices are connected.

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In order to substitute for the in availability of the MINOLTA SPAD 502, a leaf from a

section is being taken to the lab and the chlorophyll content is being measured. This data is assumed to be an average value of the real time chlorophyll content. This reading is taken two times a day and is fed as input using the USB numeric key pad. The USB numeric key pad has been used in order to exactly simulate reading from the USB sensors. This input data is used to deliver the required amounts of water and nutrients to the respective sections by mixing the correct proportions in the mixing tank and by opening the corresponding solenoid valve as mentioned in the Functional Overview and the SWARM software sections.

Figure 14: Delivery end.

2.6 Performance Analysis and Results

This section elaborates on the characteristics, properties and needs of the groundnut crop. Performance of the SWARM system has been analyzed and the results have been tabulated. The SWARM system is compared with the existing method of manual irrigation, nutrient management and delivery. 2.6.1 Introduction

Crop name : Groundnut Scientific Name : Arachis hypogaea Linn. Family : Leguminoseae

Sub- family : Papilionaceae

Groundnut originates from South America. Well-drained, light-textured, loose, friable

sandy-loam or sandy clay loam soils and a moderate amount of organic matter are ideal for its cultivation. Optimum temperature for seed germination is 30 0C.The crop can be grown successfully in places receiving a minimum rainfall of 1250 mm.

The cultivated groundnut has three distinct botanical groups:

pish

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Valencia and Virginia

Groundnut is cultivated commercially in both Kharif/rainy as well as Rabi/summer

seasons. In Kharif, the crop is grown under rain-fed conditions between May to December by planting varieties belonging to different habit groups. In contrast, during Rabi, the varieties belonging to pish bunch and valencia are preferred for their shorter duration and are grown under irrigated conditions. 2.6.2 Land Preparation

The primary tillage operations (to a depth of 25-30 cm) were performed during mid February. This operation opens the soil and preserves soil moisture by recharging from subsequent rains. A well prepared seedbed results in good germination and healthy seedlings, thus the proper plant stand is maintained. 2.6.3 Summary of the Crop Stages Sowing

The seed rate is selected (140-150 kg/ha in this case) for the Rabi crop and the sowing distance of 25 x 10 cm is determined and maintained during the sowing process. Flowering

GROUNDNUT FLOWER Flowering in groundnut begins 20 to 30 days after emergence. About 4 or 5 stages of flowering are recognized. Few flowers are produced during the first stage, followed by a stage of rapid flowering. A peak is reached at the third stage, followed by a decline.

Pollination and Fertilization Self-pollination and cross-pollination are two primary methods followed by groundnuts.

Fertilization is completed within 6 hours of pollination. Pegging

Peg is a stalk-like structure bearing the fertilized ovules at the tip. It required a week’s time for development. After this the ovary started developing into a fruit. The pegs which failed to contact the soil withered away while the successful ones developed into fruit. The Groundnut Fruit (Pod)

GROUNDNUT FRUIT The mature pod normally contains 2 to 4 seeds and itsusual size is 2.7 x 6.0 cm. The embryo, which is dormantduring peg-elongation, begins to grow 3 to 4 days after the pod begins to develop. The inner side of the shell turnsincreasingly dark brown owing to increased tannin content,finally becoming very dark brown on maturation, whichtakes about 60 days after fertilization. The optimumtemperature during pod development is 31 to 33°C.

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2.6.4 Implementation and Testing The SWARM system was tested for a period of 1 ½ months, starting from end of

February to mid April (values presented here were measured until the 11th of April, the system is still being used in the farm). We mainly monitored the flowering and pegging phase of groundnut, which was the most sensitive phase of the crop in terms of moisture and nutrient requirements. Irrigation scheduling

Irrigation is aimed at supplying sufficient water to the crop rooting zone at appropriate times to prevent soil water deficit and crop stress. This goal was achieved by measuring soil water status to schedule irrigation at a soil water potential above which the crop will not be stressed. Sensors in each section supply this information as Kc values.

The water absorbed by the groundnut during the first month after sowing is relatively small. Hence the very early growth phase is not highly sensitive to moisture stress. Thus, in the first three weeks, input from the sensor was timed as once in four days.

Vigorous flowering is the period of greatest sensitivity to moisture stress. The groundnut crop required maximum amount of water during flowering and it continues up to pod formation period. At the peak of flowering, the root system is less efficient and the demand for water is high, coinciding with the highest sensitivity. Thus, from flowering stage onwards, sensor input was read twice everyday.

The threshold Kc values during the various stages were fixed as follows: Crop

characteristic Sowing Flowering

and pegging

Pod formation

Ripening

Stage length 25

35 45 25

Kc values 0.4 1.26 1.05 0.6 Table 4: Kc values

The incoming digital inputs were checked against these threshold values and if required, the delivery system was signaled for operation. Fertilizer application

A fertilizer is any substance containing plant nutrients that are usually added to soil to supplement the required plant nutrients. Fertilizer grade or analysis is the minimum guaranteed plant nutrient content as percentage of total nitrogen, available phosphorus, and water-soluble potassium. Fertilizers may be:

• Single nutrient fertilizers or straight fertilizers: fertilizer containing only ONE nutrient element.

• Double nutrient fertilizers: those that contain TWO nutrient elements. • Complete fertilizers or complex fertilizers : materials contain the elements N, P, and

K. Nutrient requirement of groundnut was given as:

N - 16 kg/ha, P2O5 - 45 kg/ha, K2O - 45 kg/ha

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In our case, the selected fertilizer was: Urea - 46% N To solve for the mass of the fertilizer material, we used the following formula:

mass of nutrient recommended mass of fertilizer = -----------------------------------

analysis of fertilizer (%) Hence, mass of urea = 16 / (46/100) = 34.72 kg ~ 35 kg For groundnut, Nitrogen was recommended in two equal split doses:

1. At the time of sowing 2. After 35-40 days of sowing, preferably after weeding.

Based on the above information, fertilizer application was scheduled for a week, starting from 16th March to 23rd March, 2006. 5% solution of urea was used.

Description Exact Requirement

Manual system SWARM system

Water requirement(mm)

420 540 490

Urea usage 35 kg 39 kg 37.8 kg Cost of produce (Rs/kg)

28.22 27.89 28.06

Average Yield (kg/ha)

870 846 859

Table 5: Performance Results

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3. SUMMARY The basic purpose of SWARM is to create an integrated system that effects optimum

irrigation and nutrient supply to crops thus serving the dual purpose of aiding farmers in agriculture, protecting the environment from excess fertilizer pollution and conserving water. The results indicate clearly that SWARM has achieved majority of the objectives. The manual system supplies 129% of the requirement of water while SWARM delivers only 117%. A direct 12% wastage is avoided. In the case of nutrient delivery the SWARM system supplies 108% of the actual requirement while doing it manually we supply 111%, accounting for the wastage during application and other factors. Hence about 3% of the fertilizer is saved. It is clear that the wastage is less when the farm is irrigated and fertilized by the SWARM system.

The project was completed with satisfactory system implementation. The implementation was done on a medium scale by using a comprehensive hardware module and an integrated software module in a ground nut farm at Kuppam, Andhra Pradesh, India. Moisture meters were deployed in the field, nutrients was measured manually in the lab and fed to the SWARM software using a USB numeric keypad. Solenoid valves are used to control the supply of water and nutrients using the computer. Though the implementation is in a small scale, it is a close depiction of a large scale implementation. We plan to continue the deployment of the SWARM system in our test site until the crop is harvested and then move on to test it in a larger farm. 3.1 Future Research

The future prospects of SWARM are to extend the system to measure a wide range of nutrients so that the system is comprehensive. Local weather information maybe obtained via the internet in a special format to the SWARM nodes so that they consider weather forecasts while irrigating the farm. An obvious candidate for consideration in this section would be to make the farm wireless. Wireless mechanisms are being devised and software modifications are currently being tested. The Ambient 6361 wireless soil moisture/temperature station is under consideration for future use. Another area in agriculture that requires manual intervention is regarding pest control. Fields have to be manually examined everyday in order to detect a sudden attack. If an automatic mechanism is developed for monitoring the farm and to spray the pesticide it would be a breakthrough in the agricultural field.

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4. REFERENCES [1] Tamil Nadu Precision Farming Project, http://www.tnau.ac.in/horcbe/tnpfp/index.html. [2] Intel wireless vineyard project, http://www.intel.com/technology/techresearch/research/rs01031.htm[3] Biller,R.H. Reduced input of herbicides by use of optoelectronic sensors Journal of Agricultural Engineering Research. 41(4)357-362, 1998. [4] Clark, G.A., C.D. Stanley, and D.N. Maynard. Tensiometer control vs. tomato crop coefficients for irrigation scheduling. ASAE Meeting Paper 94-2118, St. Joseph, Mich.: ASAE. 1994. [5] Dukes, M. D., E.H. Simonne, W.E. Davis, D.W. Studstill, and R. Hochmuth. Effect of sensor-based high frequency irrigation on bell pepper yield and water use. In Proceedings 2nd International Conference on Irrigation and Drainage, Phoenix, AZ: 665-674. 2003. [6] Ehsani, M.R.; Upadhyaya, S.K.; Slaughter, D.; Shafii, S.; Pelletier, M. A NIR technique for rapid determination of soil mineral nitrogen. Precision Agriculture, 1, 27-234, 1999. [7] Hussaina. F, Bronsonb K.F., Yadvinder-Singhc, Bijay-Singhc and S. Pengd, “ Use of Chlorophyll Meter Sufficiency Indices for Nitrogen Management of Irrigated Rice” in Asia Agronomy Journal 92:875-879, 2000. [8] Peterson, T.A., T.M. Blackmer, D.D. Francis, and J.S. Schepers. “Using a chlorophyll meter to improve N management”, Nebguide G93-1171A. Coop. Ext. Serv., Univ. of Nebraska, Lincoln, 1993. [9] Smajstrla, A.G. and R.C. Koo. Use of tensiometers for scheduling of citrus irrigation. Proceedings of the Florida State Horticultural Society, 99:51-56. 1986. [10] Viacheslav. I. Adamchuk; Paul. J. Jasa On the Go Vehicle based Soil Sensor, University of Nebraska Cooperative Extension Precision Agriculture EC 02-178.

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http://www.tnau.ac.in/horcbe/tnpfp/index.html

http://www.intel.com/technology/techresearch/research/rs01031.htm

project mentor: dr. chitra babunathmara/ssnce_cb.pdf · water requirements of plants/crops and...

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