Real-Time Tracking and Environmental Monitoring System for Ice

Trucks using IoT Techniques

SORADA KHAENGKARN, KAMPON NONKEAW,

THANASAK WONGLOMKLANG, JIRAPHON SRISERTPOL

School of Mechanical Engineering, Institute of Engineering, Suranaree University of Technology,

111 University Avenue Muang, Nakhon Ratchasima 30000

THAILAND

Abstract: - The problems faced by ice transporting entrepreneurs are the behavior of truck drivers in driving off

the specified route and unnecessarily opening the freezing container door. Consequently, the dropping

temperature inside the container of the ice truck damaged the frozen food transportation. For this reason, rotten

frozen food because of transportation ruins the customer’s trust. This research aims to present the design of

location tracking, opening-closing container door counting system, and temperature monitoring system for ice

trucks using Internet of Things (IoT) techniques. The real-time information is visualized via a web application

for tracking and monitoring ice trucks

Key-Words: - Microcontroller, GPS tracking, IoT, Ice truck.

Received: March 17, 2022. Revised: October 15, 2022. Accepted: November 19, 2022. Published: December 12, 2022.

1 Introduction

The behavior of driving off the route and

unnecessarily opening the freezing container door of

the ice truck driver causes temperature loss in the

freezer container. This problem affects the quality of

frozen food. Therefore, developing a location

tracking system with an opening-closing freezer

container door and temperature monitoring using the

Internet of Things (IoT) for the ice truck increases

the competition in the ice truck maker industry.

M.S. Ahmed (2021), [1], studied the design of a

real-time monitoring system using an IoT platform.

This paper suggested the IoT platform for a real-

time system which includes the node, server, and

communication protocol, Message Queuing

Telemetry Transport. The real-time water quality

management system uses an IoT platform, [2], to

monitor and control water quality, such as pH,

temperature, and turbidity, for home applications.

The prototype system by the Nucleo Board Arm

Cortex-M40 development board. Behzada et al.

(2014), [3], designed and developed a low-cost

vehicle tracking and controlling system using the

prevailing cellular technologies. M. J. A. Baig et al.

This technology includes Global Positioning System

(GPS), Global System for Mobile Communication

(GSM), and Microcontroller. The system used RF

signals in a wireless sensor network to estimate the

vehicle’s location. J.F. Mendoza et al. (2017), [4],

presented an embedded software architecture in

microcontrollers for IoT in fog water collection.

Mirza Jabbar, et al., (2021), [5], studied the design

and implementation of a Peer-to-Peer (P2P) energy

trading platform using ESP32-S2 Node-Red and

MQTT protocol interface with a private Ethereum

blockchain. The real-time monitoring and

controlling of energy resources for remote locations

with no internet access. V. Change and C. Martin

(2021), [6], designed an Industrial IoT (IIoT)

Arduino sensor system to record the temperature

and location of ladle vessels for metallurgical

purposes. The Arduino microcontroller connects to

a K-Type thermocouple, Global-Positioning System

(GPS) shield, a Real-time clock, and a Bluetooth

module. Chinna Babu D. and Prakash V Carlos A.

(2018), [7], designed real-time tracking and fuel

monitoring which are implemented using IoT with

Rasberry Pi. Hernández-Morales et al. (2022), [8],

studied the design of an inspection system using IoT

design for planting. This system contains a network

processing unit and a low-cost application. Nawzad

K. Al-Salihi (2021), [9], investigated the positioning

tracking module of IoT and GPS using Arduino Uno

and connected WIFI by ESP8266. Amit Kumer

Podder (2021), [10], reported the smart AgroTech

system using IoT to monitor urban farming

parameters, i.e., the air humidity and soil moisture.

This research presents the design and development

of the location tracking and monitoring system

using the IoT platform for the 1.65 x 2.25 x 1.66-

meter ice truck, as shown in Fig.1. The temperature

of the freezing container, the opening-closing state

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DOI: 10.37394/23209.2022.19.31

Sorada Khaengkarn, Kampon Nonkeaw,

Thanasak Wonglomklang,

Jiraphon Srisertpol

E-ISSN: 2224-3402

297

Volume 19, 2022

of the doors, and the speed of the ice truck are

recorded on the SD card.

Fig. 1: Ice truck

2 Materials and Methods

2.1 Architectural Concept Design

The location tracking and monitoring system are

designed for the ice truck using the IoT platform.

The system has sensor nodes, e.g., door and

temperature sensor, GPS, clock modules, and

actuator nodes, e.g., magnetic sensor and active

buzzer, an architectural concept design, as shown in

Fig.2. The Arduino Uno R3 is used as a

microcontroller to implement with the devices and

transfer the data (location, temperature, door

opening-closing status) to the NodeMCU V2 and

recorded on SD Card. In the opening-closing

container door monitoring, in the case the door is

opened, the active buzzer module will be alert until

the door is closed. The data is also delivered to an

online database using Message Queuing Telemetry

Transport (MQTT) via pocket wi-fi with IEEE

802.11 wireless communication standard. The real-

time data is displayed on the Web application. The

various module data and sensor statuses are

displayed on the TFT LCD, which is interfaced with

the Arduino Mega 2560 controller.

Fig. 2: Architectural concept design for local

tracking and monitoring system

2.2 Experimental Setup

Input signals for Arduino Uno R3 consist of a GPS

module as GPS Ublox NEO-7M has a 2.5-meter

positioning accuracy, a 0.1-meter velocity accuracy,

and 0.25 Hz to 10 MHz of signal frequency. In a

Clock module as DS3231Real Time Clock, the

discrepancy is at most two ppm (2

sec/1,000,000sec). The Door sensor as Magnetic

Reed Switch BR-1021 has a detection distance

value of 0 to 21 mm. The digital temperature sensor

as DS18B20 has an error of ± 0.5 °C and an

accuracy of -10 °C to +85 °C, as shown in Fig.3.

The display module is used Inch TFT Color Screen

M-320x480 with Kingston Memory Card Micro SD

SDHC 2 GB, as shown in Fig.4. The NodeMCU V2

with Wi-Fi ESP8266 receives data and transfers it to

the online Database. Fig.5 demonstrates the display

module, sensors, microcontroller, location tracking,

and buzzer module as an alarm signal and

monitoring system. SD card is used Kingston

Memory Card Micro SD SDHC 16 GB Class 10.

Fig. 3: Input module and sensors

Fig. 4: Display module

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Sorada Khaengkarn, Kampon Nonkeaw,

Thanasak Wonglomklang,

Jiraphon Srisertpol

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Volume 19, 2022

Fig. 5: Control box and sensors

2.3 Sensor Installation

Three door sensors, such as Magnetic Reed Switch

BR-1021, were installed near the doors to detect

door opening-closing status, and three digital

temperature sensors, DS18B20 attached to the ice

truck, as shown in Fig.6. 3.5-inch TFT LCD in the

driver's cabin and the control box installed beneath

the driver's seat.

a) Position sensor installation scheme

b) Position sensor installation at the ice truck

Fig. 6: Sensor installation

2.4 Programming

The GPS module, door sensor, clock module, and

temperature sensor signal-receiving write C/C++

programs, and the internet connects via NodeMCU

V2. MQTT delivered the data to the online database

using IEEE 802.11 standards via pocket wi-fi. The

information is displayed on the TFT LCD and the

web application. There are three display sections,

time duration and the number of door openings

graph, and real-time temperature graph, route

coordinate, speed, and opening-closing of doors

location on the map, as shown in Fig.7.

Fig. 7: Web application display

3 Experimental Results

The two experiments verification for a location

tracking and monitoring system.

3.1 Laboratory Tests

The temperature sensor test was performed in static

calibration, random and sequential testing at 10 – 80

C with ±1.55 C overall error using the water bath

test station, as illustrated in Fig.8. The magnetic

reed switch BR-1021 is utilized to detect the steel

door's opening-closing status. The distance between

the head probe and the magnetic probe is effectively

on/off in the 0-20 mm range.

Fig. 8: Water bath test station

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Volume 19, 2022

The GPS Ublox NEO-7M module testing compared

to coordinate on Google Maps must be within the

acceptable limits of a 5-meter position error and 10

km/h speed error. The test considered the

coordinates of 12 points around Hospital road,

Suranaree University of Technology, as shown in

Figure 9.

Fig. 9: GPS module testing Route

In the stationary position test, the highest position

error was found at 3.25 meters at position 11. The

moving position testing at a motorbike's constant

speed of 30 km/h found the 30.98 km/h maximum

speed and the 26.97 km/h lowest speed. The result

has a maximum speed error of 3.03 km/h, as shown

in Figure 10.

Fig. 10: GPS speed graph

3.2 Field Tests

Field testing of ice delivery driving location tracking and

monitoring systems. The test location is around the

university. as shown in Fig.11.

Fig. 11: Route and stopping positions of the ice

truck

The monitoring system will display the temperature.

Door open/close status, Wi-Fi status, and alerts on the

TFT LCD are shown in Fig.12. The web application can

illustrate each position's stop position and door status, as

shown in Fig.13, 14. The data record of the SD card can

save as a text file. In addition, the opening-closing status

of each door is shown in Fig.14. The temperature profiles

of the ice truck traveled as shown in Fig.15, and the

speed profiles of the ice truck were recorded as shown in

Fig.16.

Fig. 12: TFT display

Fig. 13: Location field testing on Web application

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Fig. 13: Web application display of door opening-

closing status

Fig. 14: Door opening-closing status from SD card

Fig. 15: Temperature profiles from SD card

Fig. 16: Speed profiles of the ice truck from SD card

The Ublox NEO-7M GPS module testing records

data to the SD Card module, compared with the

location on Google Maps, found the 3.25-meter

maximum position error. The sound alert system

testing of the Active Buzzer module, when the door

is opened, the buzzer is alarmed until the door is

closed. The data is transferred from the

measurement and data collection kit through the

Pocket WI-FI wireless network to the server using

the MQTT protocol. The data displayed via the web

application is efficient. Recording results to the SD

card ensures that the data will be recovered in case

of online transmission is not possible.

4 Conclusion

According to the laboratory and field test results, the

system can correctly display and notify the truck

location, temperature, and opening-closing door

status on the TFT color screen M-320x480 and the

web application with all data recorded on the SD

card. The low-cost real-time location tracking and

environmental monitoring system of the ice truck

using IoT techniques can increase the competition in

the ice truck maker industry and provide the

innovation for ice transportation services to be more

efficient.

Acknowledgment:

This research was supported by the Suranaree

University of Technology (SUT) and the Krao

Karnchang Co., Ltd.

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Thanasak Wonglomklang,

Jiraphon Srisertpol

E-ISSN: 2224-3402

301

Volume 19, 2022

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DOI: 10.37394/23209.2022.19.31

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Thanasak Wonglomklang,

Jiraphon Srisertpol

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