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A WIRELESS SENSOR NETWORK APPROACH TO MONITOR PROCESS TEMPERATURE IN COMPOSTING HEAPS Ananth Saradhi1, Rakhee2*, P. Sankar Ganesh3 1

Department of Electronics and Communication Engineering, 2Department of Computer Science and Information Systems, 3Department of Biological Sciences

Birla Institute of Technology and Science, BITS-Pilani, Hyderabad Campus, Jawahar Nagar, Shameerpet Mandal, RR District, Hyderabad 500 078, India *Corresponding author

Abstract Wireless sensor network (WSN) is a collection of sensor nodes which forms a wireless network and cooperatively monitors events and phenomena. We have explored the possibility of developing a WSNbased system to monitor temperature in compost heaps. The WSN-based system is a configuration of nodes. Each node measures the process temperature from multiple points in a composting heap using multiple thermocouple based temperature sensors that are connected to its input terminals. The analog information collected by each node is digitized and transmitted to a central hub connected to a computer, via the wireless sensor network. An option is provided for the nodes to perform additional network related functions like routing and security. Keywords Wireless sensor network, remote monitoring, temperature monitoring, Dynamic source routing, ns-2 network simulator, composting

1. Introduction One of the most versatile and remunerative techniques for handling biodegradable solid wastes is aerobic composting. Usually, in a composting system, the temperature rises to 50-70oC. The temperature within a composting mass determines the rate at which many of the biological processes take place. The high temperature rise during composting destroys pathogenic microorganisms and prevents fly breeding. When the temperature of a composting system reduces from its peak, the contents are turned in order to ensure uniform microbial activity all through the composting

mixture. By the above assertions, it is evident that temperature is one of the major abiotic factors that directly influence the composting process. However, there are fewer or no systems to accurately measure the composting process temperature are still lacking. As a result, the process is not properly controlled, thereby escalating the time and economics of composting [1]. A wireless system allows for undisturbed remote monitoring of temperature in the compost heaps. This is also scalable and provides more accurate measurements than readings taken manually with conventional (mercury/alcohol) thermometers or thermocouple based probes. The requirement for turning the compost, which is a labor intensive activity, could be identified accurately, saving enormous operating cost [2]. Moreover the composting process could be controlled meticulously in order to get the desired end product [3]. A wireless sensor network is a collection of sensor nodes which forms a wireless network and cooperatively monitors events and phenomena. Wireless sensor networks have been applied successfully in many monitoring applications in the area of bioprocess and environmental engineering. We have explored the possibility of developing a WSN – based system to monitor temperature in the compost heaps. This system monitors the temperature using sensor nodes that form a wireless network as described below.

2. System architecture Composting is usually done in heaps of size 1.5 x 1.5 x 1.5m. When the process proceeds, the temperature in the heap increases. In the conventional temperature monitoring systems, either hand-held

thermometers or thermocouple based temperature probes connected to digital meters are used. In the proposed system, the nodes that contain thermocouple based temperature probes will be placed in the composting heaps in three different locations viz., top, middle and bottom of the heap, as depicted in Figure 1. The node that is placed at the top of the heap acts as the cluster head, which receives information from the other two nodes located in the middle and bottom of the heap. The data acquired by the cluster head must be routed to the destination using routing protocols. In the proposed system, the Dynamic Source Routing (DSR) protocol will be employed.

3. Dynamic Source Routing (DSR) DSR is a routing protocol for wireless mesh networks. It uses source routing instead of relying on the routing table at each intermediate device. Determining source routes requires accumulating the address of each device between the source and destination during route discovery. The accumulated path information is cached by nodes processing the route discovery packets. The learned paths are used to route packets. This protocol has two major phases, which are Route Discovery and Route Maintenance. A Route Reply would only be generated if the message has reached the intended destination node (route record which is initially contained in Route Request would be inserted into the Route Reply). To return the Route Reply, the destination node must have a route to the source node. If the route is in the Destination Node's route cache, the route would be used. Otherwise, the node will reverse the route based on the route record in the Route Reply message header (this requires that all links are symmetric). In the event of fatal transmission, the Route Maintenance Phase is initiated whereby the Route Error packets are generated at a node. The erroneous hop will be removed from the node's route cache; all routes containing the hop are truncated at that point. The Route Discovery Phase is re-initiated to determine the most viable route.DSR is designed to restrict the bandwidth consumed by control packets in ad hoc wireless networks by eliminating the periodic table-update messages required in the table-driven approach. The major difference between this and the other on-demand routing protocols is that it is beaconless and hence does not require periodic hello packet (beacon) transmissions, which are used by a node to inform its neighbors of its presence.[7] The disadvantage of this protocol is that the route maintenance mechanism does not locally repair a

broken link. Stale route cache information could also result in inconsistencies during the route reconstruction phase. The connection setup delay is higher than in table-driven protocols. The protocol performs well in static and low-mobility environments.

4. Implementation of DSR protocol The following functions describe the sequence of events that happen during route discovery. These functions understand the flow of RREQ and RREP packets. 1. sendOutRtReq() handles sending out Route request(RREQ) packets to discover new routes. 2. handleRouteReq() is responsible for actions taken when a node receives a RREQ. By above steps, its clear that how the routes are stored in DSR. It uses route_cache variable of DSRAgent. The route cache related fields and operations are present in routecache.cc and routecache.h. The main functionality of DSR protocol for packet transmission is: 1. Transmit packet by finding the shortest route from its routing table: handlepacketwithoutSR() in dsragent.cc 2. Receive a packet: recv() function of DSRAgent. This is one of the most important function which forms as a “forking” point for most of the activities. 3. Forward a packet: The function DSRAgent: handleForwarding() in dsragent.cc under NS-2 code. DSR is based on an initial flooding of the network with the route request and then generates route replies from the destination back to the source (Figure 2). There is no route maintenance phase and the control messages have fixed length. Concise information about the two phases are given below: (i) Route Request: When the source wants to find a destination it floods the network with a short message announcing this. The message contains the source ID, the destination ID and the ID of the request. Thus, the length of the message remains constant during the route request. (ii) Route Reply: The destination will eventually receive one of the route request messages. It only knows that there exists a path and it is not interested in what the path is. The destination just returns a route reply to the neighbor from which it received the route request message. The message contains a supplementary field that indicates the number of hops it traveled so far. Each node that receives a route reply,

increments the hop count of the message and then forwards the message to the neighbor from which it got the original route request. The sensor nodes are responsible to “remember” where the flooding message came from.[8]

5. Simulation of the proposed system The proposed wireless temperature monitoring system will be simulated using ns-2 network simulator to measure the performance of DSR in this application prior to its on-field implementation.

8. Disadvantages In comparison to existing manual systems, the implementation of the proposed system will incur increased initial cost to the tune of around 30%. It necessitates retraining of personnel in careful handling of instruments and measuring the data, which further adds to the overall cost.

6. Expected Results The implementation of this system will enable continuous monitoring of process temperature in the compost heaps at a measurement frequency that can be varied. Additionally, the precision and accuracy of the temperature data will be more compared to that obtained from the conventional measurement systems.

Figure 1: Schematic representation of the compost heap with sensor nodes and cluster head

7. Advantages In addition to the others, the major advantages of the proposed system are the following: The proposed implementation is scalable and significantly reduces the cost of labor. It enables the generation of the history of data thereby simplifying process modeling and data analysis. Being a remote monitoring system, it prevents the exposure of personnel who work on compost yards to air-borne pathogenic organisms present in the compost yards [5]. With continuous monitoring of the temperature, the composting process could be meticulously controlled particularly in terms of the turning frequency, which is one of the costliest steps in the composting process. As a result, the time taken for the process to complete and the cost of the overall process could be hugely reduced [6]. In the nodes, if the temperature probes could be replaced with probes that could measure other parameters like moisture content, pH, etc., the system could be employed for measuring these parameters as well without much additional costs. Being robust and remote-monitored, the system could be used to measure various parameters in all the climatic conditions, which will be otherwise a challenging task for the human labour with the conventional measuring systems.

Figure 2: Routereply and route request of the DSR Protocol

9. Conclusion Application of wireless sensor networks to measure temperature in the composting systems was proposed. The system uses DSR protocol for routing data collected from the nodes to the receiving station. Further the simulation shall be done using ns-2 network simulator before implementing the system in field. The preliminary calculations in the economics of the system envisage an increase of around 30% in the infrastructure costs. However, from a long term perspective, this additional cost could be recovered by improving the efficiency of the composting process and also by adding probes that could measure other process parameters.

10. References [1] Sankar Ganesh P, “Some applications of bioprocess engineering in solid waste management”, PhD thesis, Pondicherry University, India 2008. [2] Puyuelo, B, et al., “A new control strategy for the composting process based on the oxygen uptake rate”, Chemical Engineering Journal (2010), doi:10.1016/j.cej.2010.09.011 [3] Ferial M. Rashad, Walid D. Saleh, Mohamed A. Moselhy, “Bioconversion of rice straw and certain agroindustrial wastes to amendments for organic farming systems: 1. Composting, quality, stability and maturity indices” Bioresource Technology, Volume 101, Issue 15, August 2010, Pages 5952-5960 [4] E. Giusti, S. Marsili-Libelli, “Fuzzy modelling of the composting process” Environmental Modelling & Software, Volume 25, Issue 5, May 2010, Pages 641-647 [5] L.J. Pankhurst, U. Akeel, C. Hewson, I. Maduka, P. Pham, J. Saragossi, J. Taylor, K.M. Lai “Understanding and mitigating the challenge of bioaerosol emissions from urban community composting” Atmospheric Environment, In Press, Corrected Proof, Available online 29 September 2010.

[6] Mengchun Gao, Bing Li, An Yu, Fangyuan Liang, Lijuan Yang, Yanxia Sun, “The effect of aeration rate on forcedaeration composting of chicken manure and sawdust” Bioresource Technology, Volume 101, Issue 6, March 2010, Pages 1899-1903 [7] http://en.wikipedia.org/wiki/Dynamic_Source_Routing [8] N. Sengottaiyan, Rm.Somasundaram, S. Arumugam, "A Modified Routing Algorithm for Reducing Congestion in Wireless Sensor Networks", in European Journal of Scientific Research, ISSN 1450-216X Vol.35 No.4 (2009), pp.529-536, © EuroJournals Publishing, Inc. 2009 [9] J. Broch, D. Johnson, and D. Maltz, “The dynamic source routing protocol for mobile ad hoc networks, Dec. 1998, iETF Internet Draft (work in progress). http://www.ietf.org/internetdrafts/draft-ietfmanetdsr-01.txt