VLIT NODE – new technology for wireless sensor network Zbynek Krivanek, Karel Charvat, Jan Jezek, Marek Musil Czech Centre for Sceince and Society E-mail:
[email protected] Introduction In the last decade an increasing importance of meteorological measurements in agriculture are stressed due to rapid weather changes. There is a need for immediate access to relevant local weather information and the possibility of its on-line analysis. There are currently no meteorological data of sufficient extent available for managing crop production. The data should be included in specific agro-meteorological models. There is also lack of adequate systems and support of the management of agricultural production based on agro meteorological models. There is a need to establish a network of local sensors and weather stations in order to support farmers. Advanced technology of in-situ monitoring must be supported by the development of skills of assimilation with the agro-meteorological models in real time. At the same time, integrating measurements from meteorological sensors and data from existing agro-production networks opened new opportunities for farmers to increase the quality of their production. This will increase their market competitiveness. Monitoring of agro meteorological elements has a strong influence on the management of growth and development of crops, but also reflects the dynamics of other important biological features including plant disease and pest incidence. It is necessary to develop methods to monitor the development of climate data collection and to assess weather conditions. Representative samples from meteorological stations located on land monitoring data must then be integrated into the production database. Typical applications for crop growth control are aimed to assess the availability of nutrients in the soil (e.g. Prefarm system) and the control of diseases and pests in the soil and crops throughout the growing season until harvest. Integrating measurements of soil and environmental conditions in the agronomic decision support model for optimal planning of activities is missing. Assimilation of real data (from sensors and satellites) in the growth model is currently the subject of research (e.g. the Future Farm project in the 7th Framework Programme for Research and Development). In recent years, there were proposed several approaches to data assimilation in real meteorological models. They are using methods including 3D-Var, 4D-Var and Kalman filter-Ensamble. Each of these methods has its advantages and disadvantages that should be evaluated in small scale models. In practice this means that the farm management system (FDMS) used by farmers and / or service organizations (Prefarm) are supported by a comprehensive system of data collection (CDC). They integrated end-user through the visualisation of geographic information system (GIS). The effectiveness of all FDMS can be evaluated based on their ability to provide relevant, accurate and timely information (e.g. weather, soil conditions and crop condition in real time).
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Basic requirements to be addressed are: •
To design an optimal sensor network for collecting agro meteorological data at farm level density, which can monitor local impacts;
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To design optimization parameter measurements guaranteeing the possibility of local modelling;
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To ensure communication between sensors and data transmission via mobile unit to the server;
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To standardise interface for integration of sensor measurements with other data;
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To integrate with Prefarm through open OGC protocols;
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Modularity solution.
Sensor networks Currently, there is a number of technologies, protocols and standards for building wireless sensor networks. Sensor networks are generally seen as cloud of mutually communicating measurement units that are capable of measuring one or more physical parameters. Each measuring unit consists of a communication node ensuring the communication with other units of measurement and its own sensor. The communication nodes are built on different platforms. Their drawback is that they are able to guarantee the communication between sensors of only tens of meters. This reduces the network ranges and the networks are not affordable. Sensor Network Systems provides a novel paradigm for managing, modelling and supporting complex systems requiring massive data gathering. It has pervasive and persistent detection/monitoring capabilities. In recent years, a growing emphasis has been steered towards the employment of sensor networks in various technological fields e.g. aerospace, environment monitoring, homeland security, smart buildings. A significant amount of resources has been allocated for national (e.g. USA, France, Germany) and international (e.g. European Commission) research programmes targeted at developing innovative methodologies and emerging technologies in different application fields of wireless sensor network. The main features that a sensor network should have are: •
each node should have a very low power consumption, the capability of recharging its battery or scavenging energy from the environment, and very limited processing capabilities;
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each node should be allowed to go in stand-by mode (to save as much battery as possible) without severely degrading the connectivity of the whole network and without requiring complicated re-routing strategies;
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the estimation/measurement capabilities of the system as a whole should significantly outperform the capabilities of each sensor and the performance should improve as the number of sensors increases, with no mandatory requirement on the transmission of the data of each single sensor towards a centralised control/processing unit; in
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other words, the network must be scalable and self-organising, i.e. capable of maintaining its functionality (although modifying the performance) when the number of sensor is increased; •
a sensor network is ultimately an event-driven system, important is to guarantee that the information about events of interest reaches the appropriate control nodes possibly through the simplest propagation mechanism not necessarily bounded to the common OSI protocol stack layer;
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congestion around the sink nodes should be avoided by introducing some form of distributed processing;
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the information should flow through the network in the simplest possible way, not necessarily relying on sophisticated modulation or multiplexing techniques.
Summarising, the fundamental requirements of a sensor network are: •
Very low complexity of elementary sensors, associated with a low power consumption and low-cost;
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High reliability of the decision/estimation/measurement of the network as a whole;
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Long network life-time for low maintenance and stand-alone operation;
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High scalability;
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The resilience to congestion problems in traffic peak conditions.
An extensive research and development work has been done in the past. It includes ensuring information technology use in agriculture; long range wireless sensor network creation for specific agricultural use, ensuring a PA technological leap, solving pressing problems for agriculture and making PA widely available for farmers, even for low scale use (cranberry fields, fruit gardens, bee-gardens etc.). However, for existing solutions the following problems remain: •
Existing WSN solutions are in experimental development phase; their implementation is not possible without the specific WSN technology developers’ assistance.
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Existing WSNs have a short working range (ability to guarantee communication between sensors only at a range of several tens of meters); therefore their implementation in large area is very expensive.
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Existing WSN technology application programming is not possible without deep WSN operating system (open source Tiny OS, commercial ZigBee etc.) knowledge, that is possible only in specialised development centres;
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Presently known WSN physical node technologies with several hundred meters working range don’t support available operating systems;
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Existing WSNs are not suited for climatic and geographical factors as well as production manufacturing problems; ICT FOR AGRICULTURE, RURAL DEVELOPMENT AND ENVIRONMENT
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Realistic WSN implementation is unthinkable without specific WSN technology that includes physical nodes, sensors, operating system, application programming environment and competence centre support.
It is clear, that new development is necessary. Development would include: •
New sensor nodes with communication ranges of 200-800m depending on environment, weather conditions and sensor location, that are suited for use in most of the European countries;
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Development of operating system programming that would collect data from sensor nodes and transport them via wireless network to base computer, communication protocol configuration that would comply with respective usage target environment, as well as specific usage application programming development in the utmost simplified environment (in language C with possibly minimal specific knowledge about operating system and WSN physical realisation) that would ensure sensor control and communication between sensor nodes.
Requirements for agriculture sensor networks From the analysis of projects there are the following requirements: •
The size of transmitted data (own measurements of sensors i.e. type sensor and the measured value) - approx 6B for one variable and one measurement;
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Measurement will always be started by the AP (gate);
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The data will be reading the AP point in periodic intervals, which can be configured. The shortest possible interval is 60 seconds;
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It is not necessary to encrypt the data due to their nature;
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Radio reach point must be at least 300 meters in open terrain and line of sight (the field, meadow);
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Estimated vastness of the network will be in the tens of elements. The elements must withstand work without charging at least 6 months (roughly agricultural season) provided data collection at least once every 2 hours;
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Easy operation of network elements (nodes);
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Mechanical resistance network elements.
As a minimum solution is required: Communication in the range of about 500 m and 250 m in the field of forest; •
Two modes of operation - on-demand, event-driven;
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Support for multihoping;
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Integration of memory;
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The possibility of simple computational operations;
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Easy integration of sensors measuring;
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Life of at least 6 months;
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The ability to connect to existing mobile solutions;
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Integration into the Web environment;
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Operating frequency of 868 MHz;
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It uses a very sophisticated two-way communication protocol that allows bidirectional data transfer;
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The anti-collision protocol thus allowing to scan multiple nodes simultaneously in the field of an antenna (up to 256 tags);
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The sensor contains a function measuring the level of the incoming signal (RSSI), which will extend battery life;
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Communication protocol supports Point-to-Point, Point-to-MultiPoint retranslation of the large distance across multiple devices.
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Sensor VLITnode implementation The development of thr second generation RFID offers the possibility to create a new generation communication nodes using RFID technology. Cominfo ltd. developed RFID technology with unique properties based on long-range communication and costeffectiveness. The technology known as Very Long Range Identification Tag is characterized by a working frequency of 868 MHz and protocol that supports communication in Point-toPoint, Point-to-MultiPoint and retranslation of the large distance across multiple devices. In combination with the mobile unit and the software interface is generated by Research Centre CCSS. vLite NODE represents a completely new and unique solution for the construction of mobile sensor networks. The node consists of two parts. The first is the host board for connecting the communication module and pour connectivity for data line sensors. The second part is the electronics that provides controlled power sensors and the module itself to achieve minimum energy consumption. When are transferred the measured data with standard data packet the is also carried information about the signal strength (RSSI) and the voltage level of node. Receiving of data in the observation area provides network access point that deals with other communication and data transfer. After consultation with representatives of the Agricultural and Forestry University, CCSS and Cominfo, we designed and manufactured first prototype of VLIT nodes. After the node testing, it became necessary to equip the sensor with temperature, humidity and radiation cover to avoid readings influenced by direct sunlight and wind. Currently we are working on a new version of VLITNode. One of the reasons for design changes were adding external ICT FOR AGRICULTURE, RURAL DEVELOPMENT AND ENVIRONMENT
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antenna to the upper part of node to increase range of transmission. Another modification is the use of bottom circular connectors for connecting the soil moisture sensor. Mesh protocol One of the goals of the VLIT Node project is to build an extensive network of wireless sensors communicating with the MESH topology. MESH topology enables connection of nodes to any other node in the network. This connection can be established using one or more hops. As part of the MESH topology is provided automatic configuration of network structure, reliable routing between nodes and automatic access to new nodes in the network via the existing nodes. Hop identifies the network segment, where all participants can communicate to each other without the need for routing. Multi-hop network is a network composed of several such segments, where information could be routed among the nodes. In the area of wireless networks AH-HOC is used. AH-HOC is a network where actors do not require any precreated infrastructure to be able to communicate with each other and it provides the necessary functionality for the network management. The main benefit of using mesh topology is the possibility to form redundant links, due the nature of network topology guarantee transmission of information. Mesh topology is not restrictive in the network structure and therefore simplifies the automatic compilation of links and network recovery after failure. The connection between two points in a full mesh topology can be set up whenever they are able to communicate. Mesh topology can be set up almost always. Implementation of mesh networks in practice is highly dependent on the method of communication, the technical and application requirements. Data collection in Agriculture is a major area of use of mesh networks and is often the only suitable solution for monitoring of large areas with a large number of sensors or as an additional source of data in places where fixed connections are difficult to install. Mesh networks are divided according to whether they are mobile or stationary, wireless or wired, occasional or defined (e.g. sensory). Each type of MESH network can solve a specific protocol, which is mainly different algorithm to find and build paths from the data source to the destination. Firmware microprocessor module VLIT can generally be divided into several general programme blocks. Mesh networks are a way to transmit data, voice and commands between nodes. They allow continuous connections and reconfiguration around the fallen or blocked paths by jumping from node to node until it is achieved. MESH network whose nodes are all interconnected with other nodes is fully connected network. Mesh networks differ from other networks in the fact that the parts can all connect to each other. Each node MESH network can be a router. Mesh network can be viewed as a type of temporary or occasional (ad hoc) network. Mobile ad-hoc network (MANET) and mesh networks are thus closely linked, but pose problems of MANET nodes mobility. Mesh networks are self-healing. The network can remain in operation whenever any node fails
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or drops the connection. The result is large network reliability. This concept is applicable to wireless networks, cable networks, and software interaction. Wireless Mesh Networks are the highest rank of MESH networks. They were originally developed for military applications but experienced great development. Design of Mesh networking nodes has become more modular - a single node can support multiple radio cards - each working on different frequencies. Proactive algorithms require enough memory for routing tables. In these data are stored to reach any network node. The main problem of the algorithm is then given by constructing a routing table and its updates. Their main disadvantage is the memory consumption and slow reaction to changes in the network structure. Reactive algorithms have low memory requirements, because they do not store routing algorithms for all network nodes, or even no routing information. Each connection is established just before the data transfer. Then the connection is terminated. The connection is omnidirectional. Their main disadvantages are large unexploited time in search of connection and network congestion at risk of broadcast queries. Hybrid algorithms are used as the routing table establishing a connection before transferring data. These algorithms have been developed in a large amount of effort to optimize the memory requirements of nodes, the need for frequent updating of routing tables (optimization in time and space), minimizing broadcast queries to build path. Communicating with a Web interface The communication protocol used in networks was implemented by vLite to mobile units proposed under the project WINSOC. The communication protocol was modified for the project node and vLite and it ensured the communication between mobile sensors and web environment. Custom integration of measured data is ensured through the Open Geospatial Consortium Enabling Sensor Web (OGC SWE). In this area a cooperation is envisaged with running international projects in the GEOSS (EnviroGrid BlackSee), GMES (e.g. Humboldt) and 7FP ICT (SANY, GENESIS, etc.). The project compared two concepts, the implantation of this standard to ensure interoperable server to access data at the server level and in the second variant, directly implementing this standard in mobile units. In the first solution is the implementation easier and ensures achievement of desired functionality. The second solution would represent a significant shift in the integration of sensor data into information systems (plug and play) and a significant increase of independent sensor networks. It would also mean a generational shift in the possibilities of the mobile unit and its applicability usability. The area storing and accessing data For subsequent data processing a database was designed corresponding to the current standards and recommendations of OGC and SWE for collecting spatial data and sensor. It can optimally process data services through Sensor Observation Services, Sensor Alert Services, Notification Services, etc.
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Results Currently, there were developed approx. 40 prototypes of sensor nodes and the deployment and filed testing started. Intensive field testing was provided in the Czech Republic. At this time (end of 2011), we installed the first testing node in Latvia for a customer. A testing in Italy in2012 is expected. Increasing the communication distance of sensors network from 50 meters to 500 meters will decrease the number of sensors necessary 100 times. It is an important aspect for agriculture application, where the first experiences demonstrate that use of sensors with communication distance between 500 meters and 1000 meters will be optimal distance to cover a farm. The density of sensors allows operational use of sensor network. Acknowledgement VLIT NODE - the solution was achieved with financial support from state resources provided by the Ministry of Industry and Trade of the Czech Republic; the project of the program “TIP2009” with registration number FR—TI1/523.
References Charvat et al. 2008, Spatial Data Infrastructure and Geovisualisation in Emergency Management, H. Pasman and I.A. Kirillov (eds.), Resilience of Cities to Terrorist and other Threats, Springer Science + Business Media B.V. 2008 Charvat et al., 2009, INSPIRE, GMES and GEOSS Activities, Methods and Tools towards a Single Information Space in Europe for the Environment Riga, Latvia Charvat et al. 2010, enviroGRIDS sensor data use and integration guideline www.envirogrids.net Gnip et al. 2008, In situ sensors and Prefarm system(p.255-262), conference proceeding book, IAALD AFITA WCCA2008, Tokyo , Japan. Wilson, 2005, Sensor Technology Handbook, Elsevier Inc, UK
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