Journal of Information Technology and Computer Science Volume 7, Number 3, December 2022, pp. 219-228
Journal Homepage: www.jitecs.ub.ac.id
Design of Soil Moisture Telemetry System Using cluster-based Wireless Sensor Networks
Annisa Widuri Murti Utami 1, Dany Primanita Kartikasari*2, Adhitya Bhawiyuga3, Reza Andria Siregar4, Fariz Andri Bakhtiar5
12345Brawijaya University, Malang
1annisawidurimu@gmail.com, 2dany.jalin@ub.ac.id, 3 bhawiyuga@ub.ac.id,
4reza.jalin@ub.ac.id, 5 fariz@ub.ac.id
*Corresponding Author
Received 14 October 2022; accepted 30 November 2022
Abstract. Agriculture is an art and science used to cultivate the land, grow crops, and raise livestock. Agricultural land in Indonesia has different soil quality in each region. Soil quality for agriculture can have an impact on crops. Therefore, a Wireless Sensor Network (WSN) was created to make it easier to determine soil moisture. This system can help to monitor the condition of soil moisture content. WSN applies a Cluster-Based Algorithm, and the protocol used in WSN is a Low Energy Adaptive Clustering Hierarchy (LEACH). WSN will search for the cluster head, and then the sensor node will send the results of soil moisture sensing data to the cluster head for further data aggregation. Then, the results of the aggregation data will be sent to the sink node and then forwarded to the cloud. Data aggregation can make the sink stay longer than 30 minutes than the sink node that receives data without aggregation. Sink nodes that do not receive aggregation data also use more load current than sinks that receive aggregation data. The test results of the average response time to find new cluster heads have an average time of 6023.4 milliseconds. The maximum distance between nodes to transmit data to each other is 100 meters.
Keywords: LEACH, WSN, Soil, Clustering Algorithm, Telemetry
1 Introduction
Internet of Things (IoT) and Wireless Sensor Networks (WSN) are technologies that transform the trend of modern automation that accelerates economic growth worldwide.
[1] IoT unites the components of physical devices and objects connected to the Internet in daily life. IoT connects various types of objects consisting of multiple sensors, actuators, and processors. IoT can operate independently to minimize human intervention in its operations. They can be remotely monitored and controlled. Sensors that are dedicated and wirelessly positioned in a distributed manner can be used to carry out monitoring functions, organizing and sending information to remote locations. This collection of sensors is called a wireless sensor network (WSN). Sensor nodes are made of highly independent power-dependent devices with limited capacity, and loss of power can cause a node to stop operating. When the sensor nodes are distributed over a large area, battery replacement options will be slow, costly, and even impossible.[2]
Sensor nodes transmission and packet reception activity from nearby nodes consume
220 Journal Volume 7, Number 3, December 2022, pp. 219-228 most of their energy. Therefore, the challenge encountered is developing a routing protocol scheme to save energy. Among the routing protocol schemes published in WSN data transmission, the routing protocol using clustering scheme has proven efficient.[3].
In addition, cloud technology has become part of IoT and WSN technology, serving efficient interaction and data centricity.[4] Integrating IoT and WSN with cloud computing has helped in various applications. The implementation of wireless sensor network and Internet of Things with integration of cloud computing solution has been proposed in recent year. This smart technology has been deployed to help human improve their life. Agriculture as dominant economic sectors for food production industries has vital role in maintaining the resources and landscapes of nature such as water, soil and biodiversity in the perspective of ecology. It is increasingly important for agricultural research to raise awareness of conditions leading to low productivity and problems. Adoption of internet connectivity based on IoT and WSN technology in farming practice has been triggered to reduce the need for manual intervention. [5] On a large agricultural land, a sensor cannot define the condition of the whole area. In a specific coverage area, the placement of sensor points will only represent the condition of that area. So that in observing a specific area, the monitoring system will need a group of sensors by operating as a wireless sensor network infrastructure. the monitoring process does not stop at acquiring sensor data, but how the data will be collected and stored to analyze land conditions. This requirement suggests developing an agricultural land monitoring system by utilizing data aggregation and network clustering techniques.[6, p.] Network clustering techniques have proven as an effective way to improve network performance due to their ability to extend network lifetime and increase the scalability of the wireless networks.[7]
2 LEACH PROTOCOL
While one of the examples of a routing protocol that can be used in a Cluster- Based Algorithm is the LEACH algorithm or Low Energy Adaptive Clustering Hierarchy, LEACH Protocol is a clustering-based adaptive routing protocol. In LEACH, all nodes can take roles as cluster heads. The primary responsibility of the Cluster Head is to gather information and send it to the base station or in research by Lin & Jiang called Gate Node (GN). [8] LEACH uses a hierarchical approach to organize networks into a set of clusters. The selected Cluster Head will manage each cluster. The Cluster Head will carry out the assigned tasks.[9] LEACH is designed to collect and transmit data to sink nodes, making it suitable for this research. In the LEACH protocol, a distributed cluster head selection method is used, wherefrom several existing nodes will be selected randomly, and other nodes will become cluster members. Then the cluster head info will be sent, and the other nodes will choose the cluster head to join to form a cluster. Then the cluster member nodes will collect data (data sensing) and send it to the cluster head, and then the cluster head will forward it to the sink with a single-hop communication method. The Cluster Head on LEACH can communicate directly with the sink.[10]
This study deploys a WSN with three components: sensors that take data, data collection centers (sinks), and the cloud as data recipients. The cluster-Based Algorithm is implemented on the Wireless Sensor Network (WSN), which will perform the data aggregation process. The LEACH protocol is implemented to organize the network into several clusters and manage data transmission from sensors to data collection centers (sinks).
Murti Utami et al. , Design of Soil Moisture… 221
3 PROPOSED SYSTEM
In agricultural monitoring systems, sensor nodes are installed in a network utilizing a wireless link. Sensors send data between sensor nodes that lead to the base station node, and this activity will lessen energy gradually each time the node sends information. If the sensor data transmission is carried out over a large enough area, with a large number of sensors and the amount of data that must be collected, it is essential to minimize energy dissipation, and maintaining the sensor node lifetime is critical especially. This study proposes a solution using the cluster-based LEACH routing protocol to overcome the problems encountered.
The system proposed in this research is a Wireless Sensor Network (WSN) which implements data aggregation techniques using a cluster-based algorithm. This system will have sensor nodes, cluster heads, and sink nodes. The sensor node in this system is the Soil Moisture Sensor, and the sensor node will collect moisture data from the soil over a certain period. The sensor node sends the acquired data to the cluster head instantly. The cluster head in this system is a device that receives data collection from several sensor nodes. One cluster head will only receive data from sensor nodes in the same cluster. The cluster head will collect data from the sensor node and perform data aggregation techniques to send results to the sink node. The sink node in this system is a device that will receive an aggregated data set from the cluster head. The sink node will also select the cluster head before executing the clustering process. The sink node will send the data aggregation results to the cloud. The cloud will receive the data from the sink node and display the data on the screen. Figure 1 illustrates the proposed system architecture in this research.
Figure 1 system architecture 3.1. Sensor Node Design
According to Riaz, wireless sensors consist of four essential parts: The Sensor Module as a module to sense environmental phenomena. The Processing Module works as a node that processes the data obtained. The Transceiver module function as a module that receives and transmits the required data, and the last module is the Power Unit as the power requirement of all WSN nodes [11]. The purpose system use a microcontroller, soil moisture sensor devices, nRF24L01 component, and a power adapter. Arduino UNO [12] is function as microcontroller device. Furthermore, Arduino UNO Arduino Uno has a USB port to connect with computer devices. [13]
Soil moisture sensor component has function to measure the environment condition
222 Journal Volume 7, Number 3, December 2022, pp. 219-228 during sensing phase. Figure 2 shows the design of the purpose system. There are two data collected from the sensor node, namely the ID node data and the results of data sensing. The node ID data will be sent to the base station (sink) for processing, and the ID will be selected as the cluster head. At the same time, the sensing data will be sent to the cluster head of each sensor node for the data aggregation process to be carried out.
Figure 2 sensor node design 3.2. Data Communication
The data communication module uses an nRF24L01 radio transceiver with a radio frequency band of 2.4-2.5 GHz. nRF24L01 works in the UHF band and is compatible with WSN networks characteristics due to its energy efficiency. [14] The communication module is a transmission point between sensor nodes, cluster head, and sink nodes. The cluster head transmits the data aggregation results to the sink node. The data received in the sink node will be sent to the storage component in a cloud computing environment using SIM800L GSM/GPRS module. The topology of data communication in this research shows in Figure 3.
Figure 3 data communication
Data communication between nodes uses the data structure as shown in table 1.
Node ID and data aggregation are in the form of INT, and soil moisture data use analog
Murti Utami et al. , Design of Soil Moisture… 223 data as data type. After being converted into string data, the aggregated data is ready to be sent to cloud storage.
Table 1 data structure table on the system
Data Type Data Format Name Description
int JSON id The id of the sensor node to
be sent to the sink analogData JSON kelembaban Results of sensing data from
soil moisture int JSON data_agregasi Contains the aggregation
data value sent from the cluster head to the sink
String JSON str Contains data aggregation
data values that will be sent by sink to cloud 3.3. Clustering Method
The purpose of the topology in the WSN is that the data transmission process is relied upon to develop transmission data collected by the sensor node. Therefore, suitable topologies are needed to meet the requirements needed by each system.[15]
The Algorithm used in this research is cluster-based. A cluster-Based Algorithm is a method of Hierarchical Routing Algorithms. In Clustering, the entire sensor network will be divided into several clusters or several layers. Two types of transmission are Single Hop Transmission and Multiple Hop Transmission. In Single Hop Transmission, the cluster head will directly send data to the base station (sink) without going through another cluster head. The single-hop method is the simplest transmission method without considering other information. However, this method may not be suitable for use in large-scale networks because there are limitations on the transmission distance between sensors. Whereas in Multiple Hop Transmission, the cluster head will send data to the next cluster head and then forward it to the base station (sink). This method can divide a large distance environment into several shorter distances for transmission.
So, this method is more suitable for use for networks with a larger scale. [16]
For the proposed system, Clustering is implemented on the soil moisture sensor node and cluster head in this system. The sensor node used is a Soil Moisture Sensor, and the sensor node will collect data from the ground. After the data is collected, the results will be sent to the cluster head, and then the data on the cluster head will be sent to the sink node. Clustering will be done using the LEACH routing algorithm. Sohrabi et al., in their research, divided the LEACH protocol into two phases.[17] The first phase in the LEACH protocol is the setup phase, which is the phase that selects the cluster head and forms the cluster. In Figure 4, at the initial state, the sensor node will send ID info in the form of numbers to the sink node. Then at the idle node sink stage, it will receive node id-data. Then from the idle stage to the stage of finding the Cluster Head, it will run the pilih_ch method, which will search for the cluster head.
Then the second phase in LEACH is a steady-state phase that focuses on the stages of data collection, data aggregation, and data transmission to the base station (sink). In the Running stage, as shown in the figure, the sensor node will start to send the results of the sensing data to the cluster head for data aggregation and transmit to the sink. The sinks that successfully receive aggregation data will forward it to the cloud. However, if the sink fails in receiving aggregation data from one of the cluster
224 Journal Volume 7, Number 3, December 2022, pp. 219-228 heads, the sink will assume that the cluster head is dead, which will be in the Cluster Head, out of service stage, and will start looking for new cluster head.
Figure 1 clustering finite state machine 3.4. Data Aggregation Method
Data aggregation is also responsible for boosting the usable life of a network and reducing energy consumption. There will be specific redundancies in the data accumulated by nodes in data aggregation so that this process will reduce excessive information.[18] Data aggregation processes try to acquire data through the sensor, then provide it for sink efficiently and keep minimal data latency.[19] Data aggregation in this system is a method that will manage data received from sensor nodes, and data aggregation will be served on the cluster head. In this research, the aggregation technique used is the MEAN function Equation (1), where this function looks for the average of the soil moisture data values sent to each sensor node.
Mean = 𝑑𝑎𝑡𝑎1+ 𝑑𝑎𝑡𝑎2+𝑑𝑎𝑡𝑎3+𝑑𝑎𝑡𝑎4+...+𝑑𝑎𝑡𝑎𝑛
𝑛 (1)
Where :
data1,2,3,4,n : the result value of sensor data n: the number of sensors that send sensing data
4. IMPLEMENTATION RESULT
The proposed solution has been implemented in a prototype environment. As we interested in better understanding on how LEACH protocol increase the system performance, the evaluation result to be measured are response time, energy efficiency and the distance between nodes. The first performance test was to measure response time during cluster head finding. The process of cluster head selection shows in Figure 5.
Tests for finding new cluster heads are carried out to test the program's response time to see how long it takes for the program to search for new cluster heads and if there are cluster heads that have died. This test is calculated when the program starts to run a new cluster head search until a new cluster head is found. This test is carried out ten times. The test is carried out by calculating the difference in time from when the program starts looking for cluster heads with the time when a new cluster head has been selected.
Murti Utami et al. , Design of Soil Moisture… 225
Figure 5 cluster head selection
Table 2 shows the results of the response time testing carried out ten times.
Testing is done by calculating the time difference between when the program starts looking for cluster heads with the time when a new cluster head has been selected. From the table, it is found that the average response time is 6023.4 milliseconds.
Table 2 response time table for new cluster head searches Test Number Response Time (ms)
1 6002
2 6003
3 6033
4 6028
5 6033
6 6002
7 6033
8 6033
9 6034
10 6033
The second performance test was to measure energy effiency. Sending data in a WSN network requires energy consumption. The more data passed in a network means, the greater the energy consumption required. [20] Cluster-based algorithms are algorithms that are quite often used to conduct energy efficiency research to achieve effective results. Because in cluster-based algorithms, data aggregation can be done, which is one of the advantages of cluster-based.[21] So, this test is carried out to determine whether the sink node that receives the aggregated data has better energy efficiency than the sink node that receives the not aggregated data. This test is done by trying to perform on the WSN by turning on the sink node that receives the aggregation data and the sink node that does not receive the aggregation data. Both nodes are provided with batteries with an idle rating of 4.1V and 0.37A. The power-on time from the sink that received the aggregated data was 500 minutes or 8.3 hours from 15.40 to 23:55, while the power-on time from the sink that received the data directly without data aggregation was 470 minutes, 7.83 hours from 13.10 to 21.00. So the results of
226 Journal Volume 7, Number 3, December 2022, pp. 219-228 this test indicate that the length of time for the sink that receives aggregation data is longer than the sink that receives data without data aggregation. To calculate the energy used in the two sinks used, Equation (2) is mentioned by Freeman, Ph.D. [22]
𝑏𝑎𝑡𝑡𝑒𝑟𝑦 𝑙𝑖𝑓𝑒 = 𝑏𝑎𝑡𝑡𝑒𝑟𝑦 𝑐𝑎𝑝𝑎𝑐𝑖𝑡𝑦
𝑙𝑜𝑎𝑑𝑐𝑢𝑟𝑟𝑒𝑛𝑡 (2)
Where battery life is the length of time the battery can last, then battery capacity is the battery's capacity, which is 4800 mA, and load current is the power load used. For the first sink node that receives aggregation data, the load current is 578.3 mA, and for the second sink node that does not receive aggregation, data is 613 mA. The results obtained show that the sink node that does not receive aggregation data uses a more significant power load than the sink node that receives aggregation data.
The last performance test in this study was transmission performance according to the distance between nodes. This distance test aims to find the maximum distance between nodes using the nRF240L1 communication module. The test conducted in an area full of obstacles, such as the presence of trees, buildings, antennas from other devices, and signal transmitters. The test is carried out at several different distances to find the maximal distance admissible to receive data between nodes that have been lit.
The distance used is determined based on the experiment of 1 meter, 3 meters, 5 meters, 10 meters, 25 meters, 50 meters, 100 meters, and 150 meters. The test's success is obtained from the successful receipt of data sent from the node to the sink. Of the experiments carried out, 75% of the experiments carried out succeeded in sending data without any packet loss.
4 Conclusion
The cluster-Based Algorithm for aggregating data on the Wireless Sensor Network (WSN) in this research was successfully implemented. The implementation of the Cluster-Based Algorithm in this research uses the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol applied to one sink node and nine sensor nodes. The response time for searching for new cluster heads is 6023.4 milliseconds.
The Algorithm is done by selecting two cluster heads and each forming a cluster to receive data from the sensor node; then, the soil moisture data obtained will be aggregated using the mean function, where data aggregation is done by finding the average soil moisture value from sensor nodes in the same cluster. Data aggregation saves energy from the nodes by reducing the amount of data redundancy. Then the results of the data aggregation will be sent to the cloud. The sink node also successfully forwards aggregation data to the cloud, collected from the sensor node and aggregated by the cluster head. The sink node sends data to the cloud via the GSM/GPRS communication module
Acknowledgments. The authors would like to thank all the people who support this research.
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