Path planning for data collectors in Precision Agriculture WSNs

Precision Agriculture (PA) is a challenging application for Wireless Sensor Networks (WSNs). The network has to deal with large deployment areas, multiple surface terrains with diverse requirements on information gathering such as energy consumption, and these operations need to be mostly unattended. Mobile robots (data collectors) when used in WSNs of such demanding applications enable them to handle the limited communication ranges of these tiny sensors and simultaneously cater to multiple end-user requests. In this work, we present Cognitive Path Planning (CPP) for mobile Data Collectors (DC) in WSNs to efficiently collect the sensed data in a PA application. Energy consumption is the major attribute that impacts the performance of the proposed approach, and hence, it is our target in this paper.

[1]  Weilin Li,et al.  Probabilistic roadmap with self-learning for path planning of a mobile robot in a dynamic and unstructured environment , 2013, 2013 IEEE International Conference on Mechatronics and Automation.

[2]  Weifeng Chen,et al.  INCOME: Practical land monitoring in precision agriculture with sensor networks , 2013, Comput. Commun..

[3]  Hossam S. Hassanein,et al.  A Priced Public Sensing Framework for Heterogeneous IoT Architectures , 2013, IEEE Transactions on Emerging Topics in Computing.

[4]  Hossam S. Hassanein,et al.  A novel cost-effective architecture and deployment strategy for integrated RFID and WSN systems , 2012, 2012 International Conference on Computing, Networking and Communications (ICNC).

[5]  Hossam S. Hassanein,et al.  Optimized relay repositioning for Wireless Sensor Networks applied in environmental applications , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[6]  Hossam S. Hassanein,et al.  Optimized relay placement for wireless sensor networks federation in environmental applications , 2011, Wirel. Commun. Mob. Comput..

[7]  Ratnesh Kumar,et al.  A wireless sensor network for precision agriculture and its performance , 2011, Wirel. Commun. Mob. Comput..

[8]  Steven M. LaValle,et al.  Rapidly-Exploring Random Trees: Progress and Prospects , 2000 .

[9]  Ian F. Akyildiz,et al.  Dynamic Connectivity in Wireless Underground Sensor Networks , 2011, IEEE Transactions on Wireless Communications.

[10]  Hossam S. Hassanein,et al.  Transactions Papers - Device Placement for Heterogeneous Wireless Sensor Networks: Minimum Cost with Lifetime Constraints , 2007, IEEE Transactions on Wireless Communications.

[11]  Hossam S. Hassanein,et al.  A delay-tolerant framework for integrated RSNs in IoT , 2013, Comput. Commun..

[12]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1986 .

[13]  Ananthanarayanan Chockalingam,et al.  Mobile base stations placement and energy aware routing in wireless sensor networks , 2006, IEEE Wireless Communications and Networking Conference, 2006. WCNC 2006..

[14]  Andrew Y. Ng,et al.  Task-space trajectories via cubic spline optimization , 2009, 2009 IEEE International Conference on Robotics and Automation.

[15]  Hossam S. Hassanein,et al.  Towards Augmenting Federated Wireless Sensor Networks , 2011, ANT/MobiWIS.

[16]  Hossam S. Hassanein,et al.  Routing to a Mobile Data Collector on a Predefined Trajectory , 2009, 2009 IEEE International Conference on Communications.

[17]  Oussama Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Autonomous Robot Vehicles.

[18]  Garcia-SanchezAntonio-Javier,et al.  Wireless sensor network deployment for integrating video-surveillance and data-monitoring in precision agriculture over distributed crops , 2011 .

[19]  Antonio-Javier Garcia-Sanchez,et al.  Wireless sensor network deployment for integrating video-surveillance and data-monitoring in precision agriculture over distributed crops , 2011 .

[20]  Ahmad A. Masoud,et al.  A harmonic potential field approach for joint planning and control of a rigid, separable nonholonomic, mobile robot , 2013, Robotics Auton. Syst..

[21]  Hossam S. Hassanein,et al.  Efficient deployment of wireless sensor networks targeting environment monitoring applications , 2013, Comput. Commun..

[22]  Mohammad Biglarbegian,et al.  A fuzzy logic based bio-inspired system for mobile robot navigation , 2012, 2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI).

[23]  Milind Dawande,et al.  Energy efficient schemes for wireless sensor networks with multiple mobile base stations , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).