1 Introduction

In the present era, the dissemination of new and modern technologies has made a huge impact on the lifestyle of the common people. Emerging technologies have created facilities that are tightly aligned with people’s interests like being compact, fast, smart, feature-rich, connected to the internet and convenient to use [1]. The integration of objects i.e. sensors, and transducers, together with the internet service enables an interesting technology called the Internet of Things (IoT). The term "Internet of things" was first coined by Kevin Ashton in 1999 in the context of supply chain management [2]. IoT allows objects to be sensed and/or controlled remotely across the existing network infrastructure. “Things” in the IoT can refer to a wide variety of devices. These devices collect useful data using various technologies and then communicate with other devices [3].

The contemporaneous applications of IoT provide a unique opportunity to transform a variety of domains, ranging from personalized applications like home automation, high-tech classroom, and offices at one end to service applications such as smart medical and healthcare, logistics and transportation, intelligent security, precision agriculture, etc., at the other end [4,5,6]. The unstable nature of the agricultural domain makes IoT the most appropriate enabling technology for identifying the various challenges prevalent in the current precision agricultural practices and providing their solutions [7,8,9,10,11]. The amalgamation of IoT with sensors and intelligent algorithms can provide smart solutions to the farmers regarding monitoring, tracking, controlling, fleet managing, inter and intra communicating as well as safety in the operation of tractors and other agricultural machinery in the field [12,13,14].

In the agricultural field, the tractor is one of the most important sources of power and is used for a variety of operations ranging from tillage to haulage, and that too under diverse conditions. Nowadays the majority of farmers in India and other developing countries are hiring tractors and other agricultural machines through a custom hiring center scheme or simply contracting their field operations. In this situation, the owners have to put extra attention on monitoring the field operations to avoid unintentional damage of the tractor or save his machine from theft problems. Therefore, monitoring and tracking of the tractor operation is the most primitive functionality in the agriculture field. The technology allows the tractor owners to know in real-time the current location of a tractor and by knowing this they can also analyze the tractor path for proper planning of the schedule of the task. Real-time tracking is also helpful for verifying field operations and investigating the driver’s behavior. This function can be used to the optimization of resources applied in the field.

For tracking the position of any device GPS is the key technology. The GPS uses the constellation of 24 to 32 medium earth orbit satellites to provide geo-position information to the GPS receiver by transmitting precise microwave signals anywhere on or near the earth. To compute the two-dimension or three-dimension position of an object or a device, the GPS receiver uses the triangulation technique. For a two-dimension (latitude and longitude) position, GPS receiver receives the signals from at least three satellites whereas for three-dimension (latitude, longitude, and altitude) position it receives the signals from at least four satellites. A number of researchers have used the GPS as a base sensor for developing the tracking or navigation system of an agricultural tractor. Fortunately, due to the rapid development rate of IoT technologies, lots of GPS modules were deployed on a commercial scale and available at an affordable rate [15]. There is also a very serious issue of the safety of operations in the field. Many times, due to faulty procedures or operations or lack of safety awareness, a number of accidents happened to cause injuries to workers which may be non-fatal or fatal in nature [16]. This comes to the research idea of this study, to develop a reliable as well as a low-cost IoT and radio telemetry-based embedded system for remote operation of tractor engine along with real-time position tracking and engine status monitoring of an agricultural tractor on a google map.

2 Problem definition

In recent years, India and other developing countries are facing the problem of fulfilling the food demands of the increasing population because skilled manpower is started moving from the fields to other industries as these industries are providing them many opportunities for better living [17]. The total employment in agriculture in the world has reduced from 43.7% in 1991 to 28.8% in 2018. Whereas the percentage of employment in agriculture is reducing every year in the country and it is estimated that the percentage of agricultural workers in the total workforce would drop to 25.7% by 2050 from 54.6% in 2011. In this situation, the majority of farmers in India and other developing countries are moving toward the custom hiring or contract farming system where they hire the tractor and other agricultural machinery from a third party or they contract the whole field operation. So, in a custom hiring or contract farming system, when contractors provide these services to the farmers without properly setting the tractor-implement combination to their utmost optimum conditions, a lot of questions have arrived in their minds. For example; where is my tractor? Is my tractor working at full capacity? Will service intervals be followed? Is my tractor safe from theft or any kind of unintentional damage? etc. To avoid these problems many kinds of tracking systems have been developed in the past using GPS, GSM, GPRS or other technologies which described in the upcoming sections.

3 Related work

In this segment, we discuss the research work in brief which has two aspects. The first involves the application of GPSs, while the second aspect focuses on the application of IoT in agriculture.

3.1 Application of GPS in agricultural vehicle

GPS-tracking has become widely accepted in various sectors like in military [18], surveillance system [19], transportation or logistics [20], and healthcare [21]. In agriculture also, GPS tracking is going to become a revolutionary tool for the modernization of agriculture today. There were various researchers who employed GPS in agriculture for various purposes [22], used the GPS for developing the steering control system of a farm tractor. Stombaugh et al. [23] were used the GPS receiver as a posture sensor for developing the navigation system of an automated agricultural vehicle for controlling the vehicle during high-speed agricultural field operations. Van Zuydam et al. [24] employed the GPS device for creating a driver’s steering aid for an agricultural implement. Using the GPS, he introduced a coordinate system to make a route that an agricultural implement should follow in the open field. Watthanawisuth et al. [25] employed a GPS and ZigBee wireless network to develop a real-time tractor-tracking system based on a mesh topology. Nagasaka et al. [26] also used the GPS for developing the navigation system for a rice transplanter.

3.2 Application of IoT in agricultural vehicle

IoT technology has been widely used in the agricultural sector for monitoring, planning, decision making, and management of farm operations. Application scenarios for IoT have been investigated and some of the published articles [27,28,29,30,31] over the past few years have been reported. Minbo et al. [27] proposed an IoT-based information system for agriculture, with a distributed architecture. They tracked and traced the whole agricultural production process by employing distributed IoT servers. Capello et al. [28] adopted IoTs for designing a real-time monitoring service in order to capable the end consumer to trace the product in the field. Kaloxylos et al. [29] takes advantage of the new characteristics of the ‘Future Internet’ to specify a farm management system. Ruan et al. [30] explained an IoT-based framework to appraise fruit freshness in e-commerce deliveries, which was a non-traditional retail service that faces various obstacles in transportation, due to product perishability and expensive logistics. de Souza et al. [31] proposed an automated system using the IoT which encompasses both hardware and software. This system is used for continuous monitoring and recording the operations in seed testing laboratories. Table 1 shows the comparison of IoT based systems developed by various researchers using different sensors and networks for monitoring agricultural tractors/machinery.

Table 1 Comparison of IoT based existing system
Full size table

Table 1, shows that in proposed systems mainly used GPS and BDS, were used as position sensors to acquire the location information of agricultural machinery. For integrating these sensors with an IoT-based system and to send data different kinds of wireless networks, such as GPRS (General Packet Radio Service), 3G/4G, Wi-Fi, and Bluetooth were employed. Moreover, the functions of the proposed systems are mainly based on monitoring and management, while there are fewer reports on the result of integration and how to execute the operation optimization service. In the past no one has reported research work on integration of IoT with Radio Telemetry based wireless communication for both real-time position tracking and engine control for an agricultural tractor. Therefore, this study will focus on the development of IoT and Radio Telemetry based embedded system for real-time tracking the tractor position in Google map and for controlling the tractor engine through wireless communication. The proposed system will help the farmers as well as custom hiring or contract farming center owner to real-time track the position of their tractor and also see the real-time performance from a remote location. The proposed system will also be helpful in terms of the operation of a thresher, chaff cutter, and other tractor-powered stationary machines from a safe distance. As these machines are very accident-prone, therefore this system may avoid human drudgery in the field.

4 System architecture and design

The core structure of the developed system is depicted in Fig. 1. The system was designed for two capabilities 1. For starting and stopping the tractor engine from a remote location using radio telemetry and 2. For real-time tracking of the position and monitoring the engine status on a developed web application. The overall system functionality outcomes from the interaction between the system components which were the on-board unit (OBU), web server, and web application. The OBU consists of two subunits i.e. Engine Control Sub-Unit (ECSU) and a GPS tracking Sub-Unit. The ECSU consists of a radio telemetry-based wireless transmitter and a receiver system whereas the GPS tracking Sub-Unit includes a Raspberry Pi-3 board, GPS module (U-blox Neo), and an internet modem. As the operator sends the information to a remotely situated tractor through a wireless transmitter system, the receiver receives the information and sends it to the microcontroller (Arduino Uno ATmega328P) where this information processed and accordingly turn ON or OFF the tractor engine. The microcontroller of the receiver system was connected to the Raspberry Pi-3 board of the GPS tracking device for serial communication through a USB port. Once the tractor engine started the Raspberry Pi-3 board powers up the GPS module for acquiring real-time information i.e. Longitude, Latitude, Time, Date, and Speed from numerous satellites, and sends it to the Raspberry Pi-3 Board. The Raspberry Pi-3 gathers both GPS position and engine ‘ON’/’OFF’ information and processes it after that sends it to the webserver with the help of the wireless network carrier. The GPS data were sent via the POST method of the HTTP protocol, and stored in a database of the web server. Finally, a web application was created by employing the Django, and Python languages and embedded with a Google Map to retrieve and display real-time information. As the tractor engine is ‘ON’ it gives the message on the web application that the tractor is ‘ON’ and ‘OFF’ as the tractor engine is ‘OFF’. The developed web application shows the real-time position of the tractor on Google map in the form of an array of red points that represents the coordinates of the position on the earth’s surface.

Fig. 1
figure 1

Overview of IoT based real-time tractor engine status monitoring and position tracking system

Full size image

4.1 On-board unit (OBU)

4.1.1 Engine control sub unit (ECSU)

For remote operation of the tractor engine, a Wireless Communication System (WCS) was designed and developed which consists of a wireless transmitting and receiving systems. Working of the developed communication system was based on radio telemetry (RT) transmission and for this XBee transceiver modules were employed. For this purpose, both RT transceiver modules were configured with the help of XCTU software to operate one module as a transmitter and another one as a receiver.

  • Wireless transmitting system

The transmitting system consists of an ATmega328P—8-bit, 16 MHz frequency microcontroller (Arduino Uno), an XBee module (radio telemetry module) as a transmitter, an LCD display, a potentiometer, switches, and a 6 Volt power supply. For starting and stopping the remotely situated tractor, an algorithm was written on Arduino IDE and uploaded on the microcontroller. The microcontroller gets the input information in the form of ‘ON’ and ‘OFF’ from switches of the transmitting system and processes it. After that microcontroller sends the information to the XBee wireless transmitter which passes the information to the receiving system. For developing the hardware of the transmitting system an electric circuit was developed and simulated with the help of Proteus Design Suite software as shown in Fig. 2 and the hardware of the transmitting system is shown in Fig. 3.

  • Wireless receiving system

Fig. 2
figure 2

Circuit diagram of the transmitting system

Full size image
Fig. 3
figure 3

Wireless transmitting system and its component

Full size image

The receiving system consists of an ATmega328P—8 bit, 16 MHz frequency (Arduino Uno) microcontroller, one XBee module as a receiver, one TIP transistor, one 1N4148 diode, one 3-terminals 12 Volt,25 Amp relay to connect or disconnect the tractor battery power with the starter motor, a relay shield consisting 4 relay switches to operate a DC motor in both the directions i.e. 2 relay for clockwise and 2 relay for anticlockwise direction. In this system DC motor was used to control the fuel cut-off lever of the tractor. The clockwise direction of the DC motor pulls the fuel cut-off lever up to a predefined position for stopping the engine and after a predefined time interval (5 s) the motor actuated in the reverse direction to get the fuel cut-off lever in its original position. For this purpose, an algorithm was developed and uploaded on the microcontroller of the receiving system. The circuit diagram and hardware of the receiving system are shown in Figs. 4 and 5 respectively.

  • Developed ECSU

Fig. 4
figure 4

Circuit diagram of the transmitting system

Full size image
Fig. 5
figure 5

Wireless receiving unit of an automatic engine starting system

Full size image

Complete hardware of the ECSU is presented in Fig. 6. The developed sub-unit was installed on the TAFE 4410 agricultural tractor and tested in the research farm of the Agricultural and Food Engineering Department, IIT Kharagpur, India. The transmitting system uses an external power supply of 6 Volt whereas receiving system gets the input power from the tractor battery. As the operator press the ‘ON’ switch of the transmitting system, it sends the information to the microcontroller of the transmitting system where it was processed, and after that microcontroller sends the information to the wireless XBee module to transmit it to the receiving system. After that XBee module of the receiving system receives the information and sends it to the microcontroller. The microcontroller of the receiving system processes the information and accordingly actuated the starter motor of the tractor engine with the help of a 3-terminal 12 Volt, 25 Amp relay to engage the pinion of the motor with flywheel of the engine to run it. Once the tractor engine achieved its rated speed the microcontroller automatically sends the information to the starter motor to stops its revolution and disengaged with the flywheel. For stopping the engine a high torque DC geared motor (12 V, 300 rpm and 8 Nm) in series with a rack and pinion gear mechanism was installed. The motor actuated the rack and pinion gear mechanism for a predefined time interval to move the fuel control lever to cut off the fuel supply. As the tractor engine ‘OFF’ it automatically releases the fuel cut-off lever for future operation.

Fig. 6
figure 6

The architecture of the developed Engine Control Unit

Full size image

4.1.2 GPS tracking sub-unit

The developed GPS tracking sub-unit consists of an embedded linux board (Raspberry Pi-3) as a Central Processing Unit, U-blox Neo 7–20 channel GPS module, and an internet modem. The internet modem with a 4th Generation broadband cellular network SIM was employed for the internet connection to the Raspberry Pi-3. As the tractor engine is ‘ON’, the Raspberry Pi-3 turns on the GPS module. The module requires a 5 Volt power supply, therefore a voltage regulator was employed to regulate the tractor battery power up to 5 Volt for operating the GPS module. After a warm-up period of 2–4 s (depending upon the environmental effect and presence of the satellite), the GPS module starts receiving various information i.e. Longitude, Latitude, Time, Date, and Speed from numerous satellites and sends it to the Raspberry Pi-3 after every 1 s with a frequency of 1 Hz. Data from this module comply with the NMEA 1083 protocol. The data was decoded using the GPGGA package using Python programming language. This GPGGA is referred to as Global Positioning System Fix Data. After decoding the GPS data, it was transferred to the webserver with the help of the internet. A laboratory pictorial view of the developed tracking sub-unit is presented in Fig. 7.

Fig. 7
figure 7

The hardware of the real-time tractor tracking system

Full size image

4.2 Web server

After processing the raw data from a GPS receiver, an algorithm was written on Python language for sending the real-time tractor information to the web server through a wireless network where they were stored on a database table. For this purpose, the “Digital Ocean” cloud platform service was used. The Digital Ocean provides a number of applications for creating a virtual server, out of which the “Django” application was used. Django is a high-level Python Web framework that encourages rapid development and clean, pragmatic design. The developed algorithm was uploaded to the Django application for receiving and storing the real-time information of a tractor in the database.

4.3 Web page

The front-end of the webpage was designed using the Hypertext Markup Language (HTML) and Cascading Style Sheets (CSS) and JavaScript as shown in Fig. 8. A Google Map API was also embedded on the developed webpage by using key and Google maps class provided by Google where vehicle position coordinates are presented. For making the website dynamic, Django web framework was used and a script was created in Python language for receiving the real-time tractor position data from a web server and presenting it on the Google map embedded on the developed web application as shown in Fig. 9.

Fig. 8
figure 8

Front-page of the developed web application

Full size image
Fig. 9
figure 9

Developed web application for real-time monitoring of the position of a given agricultural tractor

Full size image

5 Results and discussion

The developed system was tested on the Research farm of Agricultural and Food Engineering Department of IIT Kharagpur situated at 22° 18′ 52.36″ N and 87° 18′ 32.64″ E. The developed OBU was tested on an open field to check the strength of the wireless communication system for the remote operation of the tractor engine. It was found that the developed transmitting system was able to track the receiving system up to a distance of 100 m without any disturbance. Therefore, an operator can remotely ‘ON’ or ‘OFF’ the engine up to this range [16]. Informed that the number of accidents due to tractor and tractor-operated implements was found to be 31% followed by threshers (14%), chaff cutters (9%), and other machines (2%). In this regard, the developed system will be very helpful to avoid human drudgery during the operation of such machines. The system was also developed in such a way, that the wireless engine control system will only function when the tractor gear is in a neutral position. If the tractor gear is engaged the OBU will not work.

The developed tracking system was tested on both the tarmacadam road and the research farm. Figure 10 shows the position tracking on the tarmacadam surface whereas Fig. 11 shows the progressive real-time tracking in the actual field. The tracking system was able to receive real-time information from satellites after every 500 ms with a frequency of 1 Hz and sends it to the web server where it is stored. The stored information has been updated on the website after every 500 ms where it shows the position on the Google map.

Fig. 10
figure 10

Real-time monitoring of an agricultural tractor on a tarmacadam road

Full size image
Fig. 11
figure 11

a–d Progressive Real-time positions of an agricultural tractor on a google map at AgFE research farm

Full size image

The developed system was also validated in the actual field condition for tillering operations with a 9-tyne cultivator and 44 hp test tractor (TAFE Samrat, 4410) in a lateritic sandy loam soil field. The real-time position of the tractor in a straight run was validated in terms of the speed of operation and compared with the manual speed measurement. For validation purposes, speed of operation was measured manually by following the procedure as described in IS 10274:1993 [39] For this purpose, a 0.3 ha (30 m wide and 100 m long) area field was selected. The test field was partitioned into three plots of 10 m wide and 100 m long. After initializing the GPS tracking sub unit, the real-time speed of the tractor was recorded and compared with the manual measurement method using ten replications. The real-time speed of the tractor in different gears, engine rpm, and depth of operation are depicted in Fig. 12. The developed system was validated in three gear position i.e. 1st low gear, 2nd low gear, and 3rd low gear with 1500 engine rpm and 150 mm depth of operation, of tractor-cultivator combination. The results show that the system is able to record the data after every 500 ms. The fluctuation in the speed of the tractor was observed due to the undulations in the test plots. The maximum fluctuation was observed in the 1st low gear, engine rpm: 1500 rpm, depth of operation: 150 mm condition whereas the minimum fluctuation was observed in the 3rd low, Engine rpm: 1500 rpm, Depth of operation: 150 mm condition. To minimize the measurement error, the data collected from the three gears, engine rpm, and depth of operation combination were statistically analyzed using Eqs. 1–5 [40, 41] and presented in Table 2.

$$\alpha = \frac{\sum_{i=1}^{i=n}{S}_{i}}{n}$$
(1)
$$\delta = \frac{\sqrt{{\sum }_{i-1}^{i=n}({S}_{i}- \alpha )}2}{n}$$
(2)
$$\Delta = \left(\frac{\delta }{\alpha }\right)\times 100$$
(3)
$$\nabla = \left(\frac{{S}_{max}- {S}_{min}}{\alpha }\right)\times 100$$
(4)
$$\varphi = \frac{100}{n}\sum_{i=1}^{i=n}\left(\frac{\left|{S}_{i}- {S}_{actual,i}\right|}{{S}_{actual,i}}\right)$$
(5)

where: \(\alpha\) = mean, \({S}_{i}\) = ith value of tractor speed recorded using the developed system, \({S}_{max}\) = maximum value of tractor speed recorded using the developed system, \({S}_{min}\) = minimum value of tractor speed recorded using the developed system, \({S}_{actual,i}\) = ith value of tractor speed measure using the manual method, \(n\) = number of samples, \(\delta\) = standard deviation, \(\Delta\) = coefficient of variance, \(\nabla\) = coefficient of non-uniformity, \(\varphi\) = mean absolute percentage error.

Fig. 12
figure 12

Real-time speed of the tractor computed with the developed tracking system: a speed at gear: 1st low, engine rpm: 1500 rpm, depth of operation: 150 mm; b speed at gear: 2nd low, engine rpm: 1500 rpm, depth of operation: 150 mm; and c speed at gear: 3rd low, engine rpm: 1500 rpm, depth of operation: 150 mm

Full size image
Table 2 Statistical comparison of tractor speed measured using the developed system with manual measurement
Full size table

The results reveal that the coefficient of variance was found as 6.42%, 3.19% and 5.56% in tests 1, 2, and 3 respectively. Whereas the coefficient of non-uniformity was found as 17.52%, 7.94% and 15.56% in tests 1, 2, and 3 respectively. The small value of mean absolute percentage error as presented in the table reveals that the developed system is able to predict the speed measurement value close to the actual value. To check the accuracy of results, field data were also analyzed using the Duncan Multiple Range Test (DMRT) [42] and it was found that at 1st and 2nd low gear conditions, speed measured through the developed GPS based system was non-significant at 1% of significance level with manual speed measurement but it was significant at 3rd low gear condition. The results shows that the developed system is highly accurate and stable for measuring the real-time position of the tractor.

6 Conclusion

Present research work describes the development of IoT and radio telemetry based real-time position tracking and engine status monitoring system for an agricultural tractor from a remote location. This work was carried out at the Agricultural and Food Engineering Department IIT Kharagpur, India. The system comprised three main parts On-board unit (OBU), web server and web page. The OBU consists of two subunits i.e. Engine Control Sub-Unit (ECSU) and a GPS tracking Sub-Unit. The developed ECSU has a Wireless communication System (WCU) for the remote operation of the tractor engine. From the testing results, it was found that the developed system can operate the tractor engine up to a distance of 100 m without any disturbance. This system can be used as a safety guard to operate the thresher, chaff cutter and other tractor-powered stationary machines from a remote location. Whereas the tracking system receives real-time information from satellites after every 500 ms with a frequency of 1 Hz and sends it to the webserver where it was stored. The stored information was updated after every 500 ms and shows the real-time position on the developed website. The developed system is very accurate and stable and can be afforded by the farmers as well as custom hiring center owners for remote operation of the tractors to operate the highly human drudgery influenced machine as well as real-time tracking the position and engine status on the developed website.