A Monitoring System for Intensive Agriculture Based on Mesh Networks and the Android System ⇑ Francisco G

Computers and Electronics in Agriculture 99 (2013) 14–20

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Computers and Electronics in Agriculture

journal homepage: www.elsevier.com/locate/compag

A monitoring system for intensive agriculture based on mesh networks and the android system ⇑ Francisco G. Montoya a, , Julio Gómez a, Alejandro Cama a, Antonio Zapata-Sierra a, Felipe Martínez a, José Luis De La Cruz b, Francisco Manzano-Agugliaro a a Department of Engineering, Universidad de Almería, 04120 Almería, Spain b Department of Applied Physics, Universidad de Córdoba, Córdoba, Spain article info abstract

Article history: One of the most important changes in the southeast Spanish lands is the switch from traditional agricul- Received 12 April 2013 ture to agriculture based on the exploitation of intensive farmlands. For this type of farming, it is impor- Received in revised form 12 July 2013 tant to use techniques that improve plantation performance. Web applications, databases and advanced Accepted 31 August 2013 mobile systems facilitate real-time data acquisition for effective monitoring. Moreover, open-source systems save money and facilitate a greater degree of integration and better application development based on the system’s robustness and widespread utility for several engineering ﬁelds. This paper presents an Keywords: application for Android tablets that interacts with an advanced control system based on Linux, Apache, Wireless sensor network MySQL, PHP, Perl or Python (LAMP) to collect and monitor variables applied in precision agriculture. TinyOS 6LoWPAN Ó 2013 Elsevier B.V. All rights reserved. TinyRPL Android

1. Introduction real-time applications that operate using large datasets processed by the device or a cloud server. This mode of operation is a key as- Wireless Sensor Networks (WSNs) represent an emerging tech- pect of decision support (Antonopoulou et al., 2010; Zheng et al., nology for intensive farming. Wireless technology yields flexibility 2011) or tracing systems (Sallabi et al., 2011). Therefore, many sec- in sensor installation and network robustness, while reducing both tors may benefit from the information generated by mobile devices maintenance complexity and the associated costs (Li et al., 2011). to optimise systems and procedures. Previous work (Gómez et al., 2012) has contributed to precision The primary objective for this work is to develop and integrate a farming through the implementation of a technological platform multiplatform application for advanced precision agriculture con- based on free software for monitoring cultivation zones, such as trol and monitoring. a greenhouse or farmlands. However, current trends are converg- This paper is organised as follows: Section 2 describes the mate- ing on mobile technologies. Smartphones are a common and rials and methods used, Section 3 shows the results and Section 4 important part of our daily life primarily because they are portable, includes the concluding remarks. ubiquitous, small and light. From a social perspective, it is clear that the mobile communications are extremely relevant. The scien- 2. Materials and methods tific community is aware of such relevance, and many applications are under development in several science and engineering fields 2.1. System architecture (Dala-Ali et al., 2011; Chen et al., 2011; Monares et al., 2011). Sim- ilarly, agriculture is adopting such changes, and several agricul- Fig. 1 shows the system architecture organisation. There are tural applications have been generated (Rafoss et al., 2010) three elements: (a) sensors that measure the environmental infor- describe real-time mobile phone applications. mation; (b) wireless sensor networks that transport the data; and Furthermore, the new generation of advanced operating sys- (c) the server, which receives, stores and displays the data. tems, such as iOS or Android, have facilitated the development of (a) Sensors: The sensors measure environmental variables from ⇑ Corresponding author. Tel.: +34 950214501. the farmland air and soil. Two types of sensors are utilised: E-mail addresses: [email protected] (F.G. Montoya), [email protected] (J. Gómez), sensors integrated in the wireless devices and other external [email protected] (A. Cama), [email protected] (A. Zapata-Sierra), felipe@ sensors attached to the devices. m2mobi.com (F. Martínez), [email protected] (J.L. De La Cruz), [email protected] (F. Manzano-Agugliaro).

0168-1699/$ - see front matter Ó 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.compag.2013.08.028 F.G. Montoya et al. / Computers and Electronics in Agriculture 99 (2013) 14–20 15

Fig. 1. System architecture.

(b) Sensor network: The WSN network is composed by all the 2005). The value was corrected taking into account the bulk sensor nodes that acquire and transmit information to a spe- density since the probe is designed to provide volumetric cial node, the coordinator node (multipoint-to-point com- moisture values (Cobos and Chambers, 2010). The typical munication paradigm), which acts as the edge-routing thickness of greenhouse soils and sports fields is usually node. The coordinator node receives data from neighbouring 20 cm, so that the probe was installed to that depth. For nodes and sends it to the server through a different interface. probe installation, a greater volume of soil than the size of The sensor nodes are separated by no more than 300 m from the probe was extracted; probe was placed slightly tilted the coordinator node (Afanasyev et al., 2010) to avoid sev- to ensure ground contact, and flat side perpendicular to eral hops. Thus, we utilise the routing protocol for low the ground surface, in order to facilitate the vertical flow power and lossy networks (RPL) (RPL, 2013). The WSN uses of water. The soil was run through a 5 mm sieve before pro- 6LoWPAN tehcnology comprising low power wireless ceeding; thereby the gravel is eliminated around the probe, networks (LoWPANs) and IPv6 local area networks. The and ensures a good transmission of moisture from the 6LoWPAN is comprised of LoWPAN nodes that share the ground to the sensor (Cobos and Chambers, 2010). This sen- same prefix in the IPv6 address (the first 64 bits within an sor communicates with and is powered directly through the IPv6 address). Among the three types of LoWPANs, our study TelosB module. Thus, the module has a greater lifespan is focused on the ’’Simple LoWPAN’’ (Shelby and Bormann, when less power is consumed. The EC-20 sensor measures 2010). the volumetric water content (VWC) through the 10-pin (c) Server: The server system corresponds to the Linux, Apache, expansion connector in the TelosB module. The ground con- MySQL, PHP, Perl or Python (LAMP) paradigm. The server ductor connects with the TelosB ground pin, the excitation stores the data in a MySQL database and can simply and eas- connector with the Vcc pin and its analogue output with ily display the data to several clients through the Web or a the ADC pin. We used an audio jack as the interconnection mobile application. interface between the ground sensor and TelosB module (see Fig. 2). 2.2. System hardware (c) The server: Although any type of equipment can be used for a server, we utilised embedded architecture for portability, The following points describe the hardware used to implement better integration in a greenhouse and higher energy saving. the system. We used the Sheevaplug platform (Sheevaplug, 2013) that

(a) TelosB sensor nodes: Electronic devices supported by free software based on the ’’TelosB’’ platform have been used to deploy the WSN (CM5000, 2013) with 5 dBi-gain antennas. These devices are responsible for acquiring the data and transporting soil data (through an external sensor) as well as humidity, temperature and light (active photosynthetic radiation and overall solar radiation). The sampling time is 1 min. (b) Soil sensor: We used the humidity sensor EC-20 developed by the Decagon (EC-20, 2013) company. It is the largest sensor (20 cm) and offers higher depth and less power consumption (in the range of 2 mA and 2.5 V). Power consumption is relevant when working with WSNs. The sensor was calibrated experimentally in the laboratory as others authors did (Czarnomski et al., 2005). The moisture gravimetric was measured on soil samples, then, was compared to sensor readings, as gravimetric soil water content determination Fig. 2. The ground sensor connected to a TelosB node within the WSN. Shot at is the most accurate method (Kocˇárek and Kodešová, soccer ﬁeld test 16 F.G. Montoya et al. / Computers and Electronics in Agriculture 99 (2013) 14–20

operates using an ARM processor with 1.2 GHz, 512 MB of through the USB connection (see Fig. 3). Because the net- RAM and an embedded general purpose GNU/Linux OS work supports multi-hop links, the RPL routing protocol (Debian 6.0). The Sheevaplug equipment includes 512 MB (RPL, 2013) (IPv6 RPL) is used through TinyRPL (Tinyrpl, of memory, but for the database storage, an SD card of 8 2013). Although TinyRPL was recently implemented, GB, was included. several tests confirm that it performs similar to the Col- lection Tree Protocol (CTP), which is the default routing The sensor nodes have been tested inside a greenhouse of protocol in TinyOS (Ko et al., 2011). BLIP interacts with 115000 m2 surface, with metallic structure, of multi-tunnel type TinyRPL and initiates TinyRPL operations after a node with a ridge height of 5 m, and 4 m of lateral height, and the cover acquires a global address. Subsequently, TinyRPL defines was threelayered heat-polyethylene (800 lm thick) with thermal a route using ICMPv6 messages related to RPL (e.g., when insulating properties (Manzano-Agugliaro et al., 2009). In our TinyRPL detects the next hop for any supported target). greenhouse conditions, the study is not affected of external natural The route is added into the BLIP routing table. Thus, variables as wind, rain, dust, etc. The nodes have a protection that TinyRPL automatically finds the routes without a manual allows all sensors integrated can make all their measurements, configuration, which is a more realistic approach. When placed mainly at the top of the greenhouse, see Fig. 4, where line the system is introduced to a plantation, the node of sight have the wireless communications between the nodes positions are irrelevant (as long as they are within without suffering interferences with the vegetation or irrigation.

2.3. System software

The following points describe the hardware used to implement the system.

(a) Implementation in TinyOS: The TelosB modules were programmed with the open-source TinyOS Operating System (Tinyos operating system, 2013a). This platform is based on components architecture and operates using an event- driven execution model. The network nodes make use of 6LoWPAN protocol stack Blip (BLIP release 2.0), which is implemented in TinyOS (Tinyos operating system, 2013b). Each node was assigned an IPv6 address, and communication was supported by links comprising one or more hops across nodes depending on the wireless coverage between the node and coordinator node. (1) Coordinator node: The coordinator node was configured using the PppRouter application that uses the node as an edge router for BLIP 2.0; thus, one of its interfaces communicates through the serial link with the server Fig. 3. The Sheevaplug server shown with its USB connection to the coordinator and the other interface communicates with 6LoWPAN node (TelosB module) and an SD card that stores data for the MySQL database. For over 802.15.4. size comparison, a 5 Euro cent coin is shown. (2) Sensor nodes: The application (6LoWSoft_mote_soil20) was installed in the sensor nodes. It was based on the project discussed in Commonsense project (2013) and the application discussed in Tinyos application contrbution (2013). It was programmed to acquire data from the external soil sensor (Decagon EC-20 sensor) and integrated node sensor. Humidity data acquired by the EC- 20 sensor were transmitted through the Msp430Adc12- ClientC component and its corresponding interface. For instance, in the source code, the ADC0 pin was assigned to receive the data from the soil sensor analogue output. The highest power consumption level was observed when the radio was operating; 17.4 mA was consumed during transmission and 19.7 mA when the data were received, which justifies the activated low power listening (LPL) function (Low power listening, 2013) at each node. This function controls the radio duty cycle and facilitates better power autonomy. With LPL, a node turns on its radio during the necessary time span to detect a carrier in the channel. When a carrier is detected, the radio operates long enough to receive a complete packet. The parameter sleep_interval config- ures the time span to switch off the radio (in ms); however, despite this configuration at each node, it is unnecessary to control the coordinator node battery lifespan because it is powered by the Sheevaplug server Fig. 4. Node installation inside a greenhouse. F.G. Montoya et al. / Computers and Electronics in Agriculture 99 (2013) 14–20 17

wireless coverage), and thus the project is reproducible – Graphs.php contains functions to deliver the data to the app for for any farming installation regardless of the WSN drawing graphs. distribution. – Nodes.php contains functions to retrieve and modify motes (b) The server: The server operates using a LAMP structure. It information, such as its alias or map position. stores the data from each sensor in a database and displays Configuration files are stored in the config folder. the data through web pages coded in PHP and JavaScript. Helpers are functions used to validate input data and format This data storage approach facilitates easy access by users output data; they are in the helpers folder. to information through the Internet. The data transferred Models are used to retrieve data from the database. from a coordinator node are received through UDP sockets. No files contain views because they are not necessary for our A Python script processes the raw data and transforms it project. to the corresponding metrics (e.g., temperature is recorded Database access: The data are stored in a MySQL instance on the in Celsius). To support graphic generation, Open flash chart server. The models access this database using standard PHP–MyS- (Open flash chart project, 2013) was utilised. This tool is QL functions wrapped in the file inc.mysql.php. based on Flash technology but is also opensource and cus- Data output: There are no views in the project because the data tomisable. It shows the data in the database through statis- are output using JavaScript Simple Object Notation (JSON) (Crock- tical charts that facilitate easy data comprehension. For ford, 2006). instance, the sample dates are observed as the mouse is placed over the chart. It utilises Ajax for web dynamism and displays the data in real-time. In addition, we installed 2.4.2. Android application the PPP service for effective communication with the coordi- The android app uses Android 3.2 and higher, but we recom- nator node. Using PPP, a TinyOS node working with RPL is mend running the application with a screen 7 inches or larger. identifiable as a network interface to other host or router; Code structure: The android app also follows the MVC pattern. it facilitates communication between the edge router and There are five primary class types. server. Finally, a startup script was created to support com- Activities: The project is comprised of two activities: the munication between the server and coordinator node in splash screen and the primary activity. The splash screen order to allow the WSN information to be stored in the manages the login procedure and the primary activity man- database. ages the interaction with the action bar as well as controls (c) Web application: The web application is divided in four sec- the fragment transactions and data persistency the activity tions: Home, Values, Graphics and RTGraphic. The Home is interrupted (i.e., rotating the device or answering a call) section includes a brief description of the project with or fragments are switched. images and schemes. The Values section displays the data Fragments: Each screen or dialogue in the app is a fragment. in tables, while the Graphics section graphically stores the The fragment layouts are stored through XML; each frag- data. In both cases, the node ID and environmental variable ment manages the user interaction through views. (temperature, humidity, TSR, PAR or VWC) are indicated. A Models: The data received from the server are stored in time period can be specified using two calendar and timeta- model classes, which also contain functions to process such ble widgets. Similarly, the RTGraphic section shows the data data. acquired by a sensor in real-time and for a particular envi- Loaders: The web service connections are managed through ronmental variable. If there is a power failure in one of the Loader classes, which create a proper HTTP request, con- sensors, then an alert email is sent to a pre configured nect with the web services and retrieve the expected data. address. This works by combining data from the database Components: Two primary components were used in this and Linux Cron. project. – DropDownView.java: Manages the sidebar used for user 2.4. Mobile application selection of the node data. – MapView.java: Manages the user interaction with the While the web-based system performs optimally and has a sim- motes map displayed on the main screen. ple web interface, it is undeniable that the widespread use of mobile devices, such as tablets or smartphones, and their low UI Patterns: The application was designed following recommen- connectivity costs have rendered native applications an attractive, dations from Google on android user interaction. The navigation alternative solution. This solution would aid farmers in managing bar at the top is used to select the active screen. When a user clicks and monitoring their crops from anywhere without a computer. on one of the tabs, the appropriate fragment is loaded onto the Thus, we improved web system with a native application for An- main screen. If that fragment was previously loaded, its data were droid and mobile devices. The following sections describe the most stored when the user navigated away and are restored when it is relevant aspects that were addressed and its development. reselected. The required code for such activity is in BaseFrag- ment.java, which is an abstract class that defines a placeholder 2.4.1. Web services for code that manages fragment data storage and retrieval. It also Web services connect the Android app with the database in contains functions used by multiple fragments. which the sensor data from the nodes is stored. The application uses the services to retrieve the data and change the nodes config- 3. Results urations, such as available sensors or alerts. Code structure: The code was written considering the Model Wireless sensor networks have become an important tool for View Controller (MVC) pattern to ensure modularity and facilitate modern farmers (Coates et al., 2013). For scalar sensors conserving its further development. The code structure is as follows: energy is critical (Suh et al., 2008). The results of the implementation of LPL function for energy saving are summarised in Table 1.It Controllers are stored in the root folder PHP files. is shown that without LPL function, even lithium battery, does not – Alerts.php contains functions to manage alert reporting. last a full week, because the radio module is consuming about 20 – Authorise.php contains the login function. mA all the time. These values are similar to those obtained at 4.5 18 F.G. Montoya et al. / Computers and Electronics in Agriculture 99 (2013) 14–20

Table 1 sleep-interval of 2048 ms, it can reach more than 1 year of life; Lifetime interval (weeks) for battery type vs sleep interval (ms) although by safety, is recommended to change it at 1 year of oper- Sleep_interval (ms) Duration (weeks) ation. However, the system developed throws a warning alert if there is a power failure in a sensor. Alkaline Lithium Advances in the ﬁeld of Internet has opened up new challenges 512 9.37 13.3 as well as opportunities to fulﬁl the increasing needs for up-to- 1024 18.6 26.7 2048 37.1 53.4 date and precise information in agriculture; the greenhouse sector No LPL 0.6 0.9 is not an exception. Nowadays web tools have been developed for numerous applications in agriculture such as the diagnosis of dis- eases of the oilseed-crops (Kolhe et al., 2011), and for modelling days without LPL working in combination with similar protocols and simulation of greenhouse environments under several scenar- (CoapBlip) (Potsch et al., 2012). When implemented LPL, with ios (Fitz-Rodríguez et al., 2010). The average greenhouse farmer is

Fig. 5. Top figure: volumetric water content (VWC) measurements curve for a user-defined period of time. Bottom figure: bar chart with minimum, average and maximum VWC values for the same period. F.G. Montoya et al. / Computers and Electronics in Agriculture 99 (2013) 14–20 19 quite dedicated. The developed web application allows improving the quality of life of farmers; due they do not need to be in situ so long to control their greenhouse climate parameters. This is espe- cially important for weekends, because without monitoring system, the farmer should go to the greenhouse to ensure that everything works properly. Fig. 5 shows a web screen of server side application. In this view, VWC is monitored during several days with information of minimum, maximum and average values.

3.1. Functionality

The app main screen is the map as shown in Fig. 6. The main screen shows a list of nodes and a map that repre- sents their location. A red colour indicates that the node did not send any data to the server for the past 10 min. Nodes can be dragged around the map. When a node is clicked, the user can see more detailed information about it and its sensors as Fig. 7. Detailed information of a node. shown in Fig. 7 The user can see pretty nice graphs using (Achartengine opend source library, 2013) with sensor data (see Fig. 8). The user can also manage alerts (Fig. 9), which are conﬁgured per node and will send an email to the conﬁgured email address. The user can set alerts for each sensor in a node; e.g., the user can set an alert that sends an email when a particular node regis- ters a temperature over 40 ° for 5 min. Such alerts are also regis- tered and can be dismissed from the app by clicking on Fix.

4. Discussion and conclusions

In this work, we described and tested an Android application for monitoring purposes in intensive agriculture using wireless mesh networks. The Android application was implemented using the latest technologies in order to facilitate simple and easy management and monitoring of an agricultural system, greenhouse or golf course, among other functions. The system can simultaneously operate with several installations, which allows the manager or farmer to control the plantations through a bet- Fig. 8. Graphs with sensor data. ter decision-making process. Implementation of a full platform based on free software for monitoring farmlands using this work is an important contribution to intensive agriculture or similar. To promote and continue this work, the developed software is available for free as an opensource project (6lowsoft project, 2013).

Fig. 9. Alerts screen.

Acknowledgements

This work has been supported by the Government of Spain – Ministry of Education, Culture and Sports – High Council of Sports Fig. 6. Main screen. under reference 190/UPB10/12 20 F.G. Montoya et al. / Computers and Electronics in Agriculture 99 (2013) 14–20

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