WAMS (Wireless-sensor-network-based Adaptive Management System) is a pest control tool that makes continuous use of weather and pest monitoring information for the dual purpose of improving the knowledge on pest systems and ameliorating pest management decisions. It operates at the interface between research and pest management, establishes a close-loop between monitoring, management and analysis of systems, and automatically improves the reliability of pest control relevant predictions as soon as additional information becomes available. Population models, based on time-varying distributed delays, are at the core of WAMS. The paper identifies some important WAMS features, evaluates the predictive capabilities and its alert mechanisms as satisfactory, and reports some preliminary experiences that reveal advantages and benefits in the areas of (i) knowledge improvement and (ii) control rationalization. The preliminary experiences also point to some drawbacks and shortcomings related mainly to (i) the need of a continuous engagement of actors (growers, extensionists, applied entomologists) and (ii) the importance given to the vector in the case of the case of an economically relevant pathogen-vector-host plant system
WAMS - an adaptive system for knowledge acquisition and decision support: the case of Scaphoideus titanus / M. Prevostini, A.V. Taddeo, K. Balac, I.E. Rigamonti, J. Baumgärtner, M. Jermini. - In: IOBC/WPRS BULLETIN. - ISSN 1027-3115. - 85:(2013), pp. 57-64.
WAMS - an adaptive system for knowledge acquisition and decision support: the case of Scaphoideus titanus
I.E. Rigamonti;
2013
Abstract
WAMS (Wireless-sensor-network-based Adaptive Management System) is a pest control tool that makes continuous use of weather and pest monitoring information for the dual purpose of improving the knowledge on pest systems and ameliorating pest management decisions. It operates at the interface between research and pest management, establishes a close-loop between monitoring, management and analysis of systems, and automatically improves the reliability of pest control relevant predictions as soon as additional information becomes available. Population models, based on time-varying distributed delays, are at the core of WAMS. The paper identifies some important WAMS features, evaluates the predictive capabilities and its alert mechanisms as satisfactory, and reports some preliminary experiences that reveal advantages and benefits in the areas of (i) knowledge improvement and (ii) control rationalization. The preliminary experiences also point to some drawbacks and shortcomings related mainly to (i) the need of a continuous engagement of actors (growers, extensionists, applied entomologists) and (ii) the importance given to the vector in the case of the case of an economically relevant pathogen-vector-host plant systemPubblicazioni consigliate
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