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Livestock Location Tracking Using NBIoT

Info: 7282 words (29 pages) Dissertation
Published: 20th Oct 2021

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Tagged: Internet of Things

TABLE OF CONTENTS

TABLES ............................................................................................................................ 3-4

1.0 INTRODUCTION AND REPORT OUTLINE ................................................................. 4

2.0 LITERATURE REVIEW ................................................................................................... 5

2.1 General Overview ......................................................................................................... 5

2.2 Related works ............................................................................................................... 6

3.0 BACKGROUND THEORY .............................................................................................. 8

3.1 Adafruit Ultimate GPS module ...................................................................................... 8

3.2 Arduino MKR NB 1500 ............................................................................................... 10

3.3 The SIM card ...............................................................................................................11

4.0 OVERALL DESIGN .....................................................................................................13

5.0 DETAILED PLAN ....................................................................................................... 15

5.1 ACTIVITY TABLE ..........................................................................................................16

5.2 GANTT CHART ...........................................................................................................17

6.0 DISCUSSION ...............................................................................................................18

7.0 REQUIREMENT OF FACILITIES AND MATERIALS ................................................20

7.1 HARDWARE REQUIRED FOR THE PROJECT ..........................................................20

7.2 SOFTWARE REQUIRED FOR THE PROJECT ..........................................................20

8.0 REFERENCES ........................................................................................................21-22

TABLES

TABLE 3.1: HARDWARE SPECIFICATIONS OF ADAFRUIT ULTIMATE GPS

MODULE SENSOR ......................................................................................................... 9

TABLE 3.2: HARDWARE SPECIFICATIONS OF ARDUINO MKR NBIOT 1500...........11

TABLE 5.1 DETAILED ACTION PLAN...............................................................................15

TABLE 5.2 ACTIVITY TABLE.............................................................................................16

FIGURES

FIGURE 1: THE BLOCK DIAGRAM OF THE TRACKING DEVICE………….………….7

FIGURE 2: ADAFRUIT ULTIMATE GPS MODULE………………...…………………….9

FIGURE 3: ARDUINO MKR NB 1500……………………………………………………. 10

FIGURE 4: THE SIM CARD ……………………………………………………………… 12

FIGURE 5: THE OVERALL DESIGN……………………………………………………. .14

FIGURE 6: THE GANTT CHART OF THE PROJECT GIVING A DETAILED ACTION

PLAN……………. 17

1.0 Introduction

Livestock Location Tracking is an important topic interest for both wildlife and livestock researchers for a long time ago. Livestock location tracking allows researcher to determine some key aspects, such as the pasture utilization, knowing the behaviour and performance of the livestock [1], and to provide the location of livestock to the farmers around the landscape [2]. During the old days, livestock location relied on artificial features and human observation which are painted tag and painted pattern respectively [12]. The down side of this methods is that the famers do get tired easily and associated errors while looking for their missing livestock [1].

This project is to develop a very low power consumption and high-performance monitor that can log data regarding the location, well-being and health of the livestock to a cloud service using NB/IOT (Narrow band Internet of things). The application of NB/IOoT technology to livestock using the Arduino MKR NBIoT 1500 with a GPS shield has the possibility to change farming practice, making them more accurate, available, and capable of being sustained. The monitors shall have an extremely long battery life and provide a low data and cost solution for tracking livestock in ranch environments. In the project, the livestock tracking, and health information obtained will be stored in the cloud. As part of the project, I will evaluate several cloud storage providers, including Amazon AWS, Blynk, Thingspeak, Azure and others. Already available Low Power Wireless technologies such as SigFox and LoRa feature low power consumption but have low data rates, and sometimes limited coverage. In this project, we investigate the data rates and power consumption supported by the NBIoT technology. In addition, the NB/IoT has greater reach indoor and outdoor because it makes use of an external antenna.

The report looks to other relevant and related projects in the literature survey section. A detailed overview along with the hardware components of the project is given in the background theory section. The overall design gives a comprehensive view of the project that assists us understand how the project progresses. With the assist of the overall design I have designed a detailed action plan for the completion of the project. In the discussions, I shed more light on the difficulties that I'm currently facing. Finally, a report of hardware and software materials available till date to give the current status of the project.

2.0 Literature Survey

2.1 General Overview

Narrow Band IoT (NB-IoT) [3] was standardised as part of 3GPP release 13 in June 2016. It has been launched by several developers across the world. Vodafone Ireland announced a NBIoT nationwide rollout in August 2017 (Kennedy 2017, August) [3]. The NB/IoT domain embraces a huge number of applications with different goals, features, requirements and constraints. Before the introduction of IoT technology in contemporary age there has been different ways to track the location of livestock. They usually relied on human observation of natural (paint patterns) or artificial features (painted collar or tag) to know their livestock location [12]. NB-IoT is not the only IoT solution that is designed to handle IoT communication needs over long distances with low date rate and low power usage. After the introduction of IoT technologies, globally there are more IoT technologies rather than NB/IoT to track the location of livestock. Other examples are proprietary systems such as SigFox, Long Range (LoRa) WAN.

The computer scientist and developers worked on various approach in developing a monitoring system in which this project is all about as well.

VT-Networks [3] Ireland launched a nationwide SigFox network in 2016 providing solutions for tracking for farm assets and security sensors for gates amongst others. SigFox [4] is a proprietary, cellular-like to build wireless network for low bandwidth wireless communication system. In terms of energy consuming, it is very efficient because it consumes low power, but it provides a limited capacity that's lesser messages per day with up to 12 bytes each [4]. Its actual coverage is more on urban area with higher population density but still relatively small, particularly in rural areas.

Pervasive Nation [3] is a nationwide LoRa testbed platform setup by CONNECT and funded by Science Foundation Ireland (Doyle 2017). LoRaWAN [5] is a type of connectivity which uses unlicensed radio spectrum to enable wireless wide area network (WWAN) specification designed to allow long range communications for IoT-like applications between minimal powered sensors and gateways connected to the network. It was designed to minimize energy consumption and provides downward and upward bit-rates between 0.3 kbps to 50 kbps per channel [4]. It may be used as a private network, but it may also be used to deploy a shared service infrastructure.

LoRa provides a reasonable bandwidth, battery life and low power consumption. Its performance in RSSI-based localization is poor. Moreover, LoRa prescribes a star topology and constrains the kind of synchronization and communication between nodes and the gateways [4]. Another [11] major benefit of LoRaWAN is its low cost, although there are upfront costs associated with gateway installation, and typically annual maintenance costs, but unlike SigFox public LoRaWAN gateways do not require subscription fees which makes it more attractive for some users.

2.2 Related Works

A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd [6].

The authors developed a system that's integrated into two devices which are GPS collars connected to a LPWA network (Sigfox) and low-cost Bluetooth low energy (BLE) tags connected to those collars. The system requires some animals in the herd being fitted with GPS collars and the rest with BLE tags in which the developed monitoring system can gather, transmit, and process the location data of all animals in a herd. The authors showed us that the two integrated devices have been demonstrated to be effective in monitoring the location of each animal in a herd at a much lower cost than existing solutions. However, further research is still required to develop new utilities for the data gathered by the proposed solution.

Design of GPS-based Wild Animal's Tracking System with Reduced Size and Weight [7]

This paper describes the initial design of a wild animals tracking device (tags). The device relays on an ultra-low power, small form factor GPS receiver for accurate and precise location of wild Animal. Moreover nine-axis (gyro + accelerometer + compass) MEMS are used as an auxiliary motion sensing device. The collected GPS data is transferred by an RF transceiver working in the ISM band to a retranslating base station. As the output power of the transceiver should be as low as possible the tracking device and the base station should be located closely to each other. After reception the base station retranslates the received GPS data through the GSM/GPRS network to the personal computer for further analysis.

Figure 1: The block diagram of the tracking device [7]

The Authors were not able to overcome the time-consuming problem while gathering the necessary information of the animal under study, nevertheless they believe as the technology continues to develop, future research will succeed to overcome the difficulties.

The references in this literature survey indicate that tracking location of livestock is an active field of research and further establish the need for low cost instrumentation to allow such monitoring to be carried out more widely. Since NB IoT has been rolled out across Ireland and other countries, it may provide a better means of obtaining livestock or wild animal tracking and related data. It appears that no previous project has used NB IOT for this purpose.

3.0 Background Theory

In this section I will discuss about the NBIoT device that I'm going to use to carry out the project, which is Arduino MKR NBIoT 1500 and other blocks included in the kit, the sensor which is Adafruit Ultimate GPS module, the cloud used to save our data permanently, the software used to implement the coding on the board and the actuators in the kit used in this project. The project will progress in these stages.

Sensor and micro controllers: The Adafruit Ultimate GPS module will sense the location of the livestock and it have a microcontroller with the low-level firmware running on it. This is connected to the Arduino MKR NBIoT 1500 where they both communicate by allowing the transmission of messages between each other at regular intervals [1].

Internet gateway: To access the data wirelessly from the Arduino MKR NBIoT 1500 we need a sim card to able to provide GSM coverage where we are and allows the Arduino MKR NBIoT 1500 board to connect to the internet, send and receive SMS, and make voice calls using the GSM library.

External Antenna: Apart from the built-in antenna the GPS module posses, both the server and the GPS module have an external active antenna support which is connected via the uFL connector. The GPS module will automatically detect the active external antenna and switch over [9].

Cloud Interface and Storage: we need a cloud service to store our data because the data is always available at short time over the console, it must be stored in the cloud storage facility which allows users to access the acquired data remotely over the cloud via their computers and mobile phones.

3.1 Adafruit Ultimate GPS module [9]

The breakout of this integrated sensor is built around the MTK3339 chipset, that's highly suitable GPS modules for this project where highly sensitive tracking and low powered usage are key criteria. The key feature of it is the built-in datalogging ability, there is a microcontroller inside the module, with some empty non-volatile memory, the newest firmware now allows sending commands to do internal logging to that FLASH. Therefore, if the information is sent and being received, the microprocessor does get some rest and don't have to wake up to be able to communicate with the GPS module anymore to save power consumption. The internal flash can store about 16 hours of data, it will automatically supply data, so you don't have to worry about accidentally losing data if power is lost.

Figure 2: Adafruit Ultimate GPS module [9]

Table 3.1: Hardware Specifications of Adafruit Ultimate GPS Module Sensor

Specification

Adafruit Ultimate GPS Module Sensor Data

Input Voltage Range

3.0-5V

Consumption

20Ma

Acquisition Sensitivity

-145 dBm

Tracking Sensitivity

-165 dBm

Satellite

22 tracking, 66 searching

Bandwidth

1-10Hz

Position Accuracy

Less than 3m

Maximum Velocity

515m/s

Warm/ Cold Start

34s

Velocity Accuracy

0.1m/s

Patch Antenna Size

15mm x 15mm x 4mm

3.2 Arduino MKR NBIoT 1500

The Arduino MKR NB 1500 [10] is all-in-one hardware design board, with all the blocks likes Narrow band IoT and LTE CAT MI networks are pre connected between the platform. The kit includes all the basic accessories needed to get started, namely the hardware modules, battery, cables, and antenna. The reason for choosing this over other IoT is because it is a learning and development board which contains the ATMEL SAMD21 micro controller, designed to integrate the core's low power-consumption and high performance with the Arduino's ease-ofuse. The Arduino Software Integrated development environment (IDE) is the software to be used to programme the Arduino MKR NB 1500.

Figure 3: Arduino MKR NB 1500 [10]

Table 3.2: Hardware Specifications of Arduino MKR NBIoT 1500

Specification

Arduino MKR NB 1500

Input Voltage Range

5-6V

Programming Voltage (USB)

5V

Operating Voltage

3.3V

Dimension

61.5 X 25mm

Memory (FLASH)

256Kb

Memory (SRAM)

32Kb

Communication Protocol

LTE CAT 1

Interface

GPIO I2C, SPI, UART

Kind of connector

USB, SIM, Pin Strips

Clock Speed

32.768 kHz (RTC), 48 MHz

Analog I/O Pins

7/1

Digital I/O Pins

22

Power Consumption

30mA to 93mA

3.3 The SIM card [8]

The Subscriber Identity Module (SIM) card has an agreement with the service provider in which they provide GSM coverage to us and allows the Arduino MKR NBIoT Board to be connected to the internet which makes it receive data via SMS. The Arduino MKR NBIoT board has a slot on the back side of the module that takes a micro SIM card, and the card holder does not have a push/pull mechanism, so it may be necessary to fix the card with a small adhesive tape.

Figure 4: The SIM card location in MKR 1500 NBIoT [8]

4.0 Overall Design

Design is a major step in the development phase for any techniques and principles for the purpose of defining a device, a process or system in enough detail to permit its physical realization. Once the software and hardware requirements have been analysed and acquired, the software design involves three technical activities - design, coding, implementation and testing that are required to build and verify the project.

The overall design activities are of main importance in this phase, Initially the GPS module will the kept around the livestock. It will monitor the location of the livestock and the data from the sensor is sent wirelessly to the Arduino MKR NBIoT board via the SIM card. The GPS modules will remotely release the payload to the MKR NBIoT 1500 board that act as a temporary storage platform and then the MKR NBIoT re-routes it to the cloud service provider which hosts the data on a more permanent basis. From the cloud the end user can access the data at any time via their personal computers or mobile devices.

Monitor the location Temporary Storage Platform Of livestock and receive data using sim card

Arduino MKR NBIoT 1500 Board

The Arduino IDE software can both be run both offline and online. In this project the program of the MKR NBIoT 1500 is run while offline, so I must install the Arduino IDE software and add the Atmel SAMD Core to it. This simple procedure is done selecting Tools menu, then Boards and last Boards Manager, as documented in the Arduino Boards Manager page [10]. The below diagram shows the procedure I used to implement the Arduino MKR NB 1500 on the Arduino IDE Software I installed on my computer.

Figure 5: Installation of the Arduino MKR NB 1500 [10]

In this project I will be writing scripts to run on the Arduino IDE software using the guide of the MKRNB Library page. I will also make use of a cloud service provider for storing the data of the location of the livestock in the cloud for easy accessibility for users.

5.0 Detailed action plan

The tasks to be completed and the plan of action is shown below using the Gantt Chart and these are indicated in different colours to show the difficulty level in the tasks. These tasks were analysed, and time was allotted based on the analysis.

TASK

TASK NAME

T1

FYP tittle research

T2

Understand the requirements

T3

Hardware and Software Component Requirement and ordering them

T4

Acquired the Arduino MKR NB 1500

T5

Learning and setting up the Arduino MKR NB 1500

T6

Download and Installation of Arduino Software IDE on a Computer

T7

Learning the Arduino Software IDE interface using the Arduino MKR NB

Library

T8

Interfacing Arduino Software IDE and the Arduino MKR NB 1500

T9

Testing Light-Emitting Diode (LED) Actuator in the Arduino MKR NB

1500

T10

Acquired the Adafruit Ultimate GPS Modules

T11

Acquired the sim card

T12

Connect the device

T13

Program to read the Adafruit Ultimate GPS Modules

T14

Get the output on the serial interface

T15

Get the output on the Adafruit Ultimate GPS Modules

T16

Testing

T17

Get data on the Arduino MKR NB 1500

T18

Make changes to code

T19

Format the data for the Arduino MKR NB 1500

T20

Implementation and Testing

T21

Select a cloud storage service provider

T22

Save data on the cloud

T23

User access the data for Testing

T24

The Final Report

Table 5.1: Detailed Action Plan

5.1 ACTIVITY TABLE

Task

Start Date

Days to complete

T1

27-Sep

7

T2

04-Oct

12

T3

16-Oct

10

T4

26-Oct

1

T5

27-Oct

7

T6

03-Nov

1

T7

04-Nov

5

T8

09-Nov

1

T9

10-Nov

4

T10

14-Nov

1

T11

15-Nov

1

T12

16-Nov

1

T13

17-Nov

62

T14

22-Jan

4

T15

26-Jan

5

T16

31-Jan

16

T17

16-Feb

7

T18

23-Feb

5

T19

27-Feb

24

T20

22-Mar

50

T21

11-May

5

T22

16-May

10

T23

26-May

52

T24

02-May

116

Table 5.2: Activity Table

5.2 GANTT CHART

Figure 6: The Gantt chart of the project giving a detailed action plan

6.0 Discussion

These are the tasks that have been completed till date:

1. FYP tittle research

2. Understand the requirements

3. Hardware and Software Component Requirement and ordering them

4. Acquire MKR NBIoT 1500

5. Learning the Arduino MKR NBIoT 1500

6. Setting up the Arduino MKR NBIoT 1500

7. Download and Installation of Arduino Software IDE on a Computer

8. Learning the Arduino Software IDE interface using the Arduino MKR NBIoT Library

9. Interfacing Arduino Software IDE and the Arduino MKR NBIoT 1500

10. Testing Light-Emitting Diode (LED) Actuator in the Arduino MKR NBIoT 1500

The Arduino MKR NBIoT has been connected to my computer via a USB cable and I made used of the Arduino software IDE to install the board on the IDE. I had a few issues while implementing and testing the light emitting diode (LED) actuator in the Arduino MKR NBIoT 1500 to generate blink output of High and Low. I later discovered the command LedPin, HIGH that I used wasn't compatible with the MKR NBIoT board then I change the command to LED_BUILTIN, HIGH which makes the LED light comes up.

One of the main challenges of this project is the security aspect, that is how confidential is the monitoring system which unauthorized users won't get access to our data to be able to know the locations of the livestock and also how authentic the system is going to be sure the data derived from the SIM card are sent to the cloud. I also plan on working on the availability of our data to ensure timely and reliable access to and use of information by the end user.

Figure 7: The Arduino MKR NBIoT 1500

7.0 Requirements of facilities and materials

7.1 Hardware required for the project

Name Status

Adafruit Ultimate GPS Modules Not Acquired

Arduino MKR NB 1500 Acquired

Antenna Acquired

Sim Card Not Acquired

7.2 Software required for the project

Name Status

Cloud Storage Not Acquired

Arduino Software IDE Acquired

8.0 References

[1] Turner L.W., Udal M.C., Larson B.T., Shearer S.A. (2000) Monitoring cattle behaviour and pasture use with GPS and GIS. [online] Canadian Journal of Animal Science. Available at: https://www.nrcresearchpress.com/doi/abs/10.4141/A99-093#.XcqcRL-JLIV

[2]. Gordon I.J. Tracking Animals with GPS (2001) An International Conference Held at the Macaulay Land Use Research Institute. Macaulay Land Use Research Institute; Aberdeen, Scotland. https://www.nrcresearchpress.com/doi/10.4141/A99-093#.Xcqc5L-JLIU

[3]. John Divilly. (2018). Factors affecting the adoption of Agri-IoT in Ireland. [online] University of Dublin MSc in Management of information Systems. Available at: https://scss.tcd.ie/publications/theses/diss/2018/TCD-SCSS-DISSERTATION-2018-045.pdf

[4] Luís Nóbrega., Pedro Gonçalves., Paulo Pedreiras., and José Pereira(2019). An IoT-Based Solution for Intelligent Farming. Available online: https://doi.org/10.3390/s19030603

[5]. LoRa Alliance A technical overview of LoRa and LoRaWAN. [(accessed on 25 January 2018)]; Available online https://www.tuv.com/media/corporate/products_1/electronic_components_and_lasers/TUeV_ Rheinland_Overview_LoRa_and_LoRaWANtmp.pdf.

[6] Maroto-Molina F., Navarro-Garcia J., Principe-Aguirre K., Gomez-Maqueda I., GuerreroGinel JE., Garrido-Varo A., Dolores Pérez-Marín C (May 2018). A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd. Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6567337/

[7] Eltimir Stoimenov, Tsvetan Shoshkov, Rosen Miletiev, Ivailo Pandiev (June 2013). Design of GPS-based Wild Animal's Tracking System with Reduced Size and Weight. Available online: https://www.researchgate.net/publication/283548242_Design_of_GPSbased_Wild_Animal's_Tracking_System_with_Reduced_Size_and_Weight

[8] The SIM card. (2018)- Enable for data. [online] Available at: https://www.thingforward.io/techblog/2018-11-14-a-first-look-at-arduinos-mkr1500-for-ltenarrowband-lte-m-connectivity.html

[9] Adafruit Ultimate GPS Module. (2018) – The sensor. [online] Adafruit.com Available at: https://www.adafruit.com/product/746

[10] The Arduino MKR NBIoT 1500. (2017). Arduino Board. [online] Available at: https://www.arduino.cc/en/Guide/MKRNB1500

[11] KMPG. Agric 4.0 - Connectivity at our fingertips (2019) Connectivity-digital-innovationAustralian farming.pdf [online] Available at: https://assets.kpmg/content/dam/kpmg/au/pdf/2019/agri-4-0-connectivity-digital-innovationaustralian-farming.pdf

[13] Maroto-Molina F, Navarro-Garcia J, Principe-Aguirre K, Gomez-Maqueda I, GuerreroGinel JE, Garrido-Varo A, Dolores Pérez-Marín C (May, 2018). A Low-Cost IoT-Based System to Monitor the Location of a Whole Herd. Available at: https://www.mdpi.com/1424-8220/19/10/2298/htm

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