Monitoring of the grain crops in storage facilities through wireless communication technology
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NM-AIST
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A Dissertation Submitted in Partial Fulfillment of the Requirements for the Degree of
Doctor of Philosophy in Information and Communication Science and Engineering of
the Nelson Mandela African Institution of Science and Technology
The storage condition measurement of grain crops is almost non-invasive to date; most of the technologies can be used to monitor the storage. Electromagnetic radiation is still popular wireless technique for grain storage condition management. It has led to the way of exploring safe methods for grain storage. The studies have shown that data detection using electromagnetic techniques has been attempted from various stances such as invasive and non-invasive approaches. Most of the existing methods utilize some form of dielectric techniques. Despite the current development, there is an increasing need for monitoring large amount of stored grains. The trend indicates the grain spoilage due to the inefficiency of detecting the climate parameters such as temperature and moisture content from storage of large amount of grains. The aim of this work is to propose the method capable of monitoring the storage facility with large amount of grains through wireless communication technology. It took into account the dielectric and radio refractive quantity properties of grains, and storage prediction based on hidden Markov for the elegant monitoring of the stored grains. The model was designed and implemented based on ZigBee technology for remote communication, where wheat is considered as the prime cereal grains for storage in large quantity. It is also tested based on the robustness, accuracy and precision to confirm its viability in real time. The results showed that the proposed method is robust in response to the climatic changes in the storage and is capable of monitoring the storage condition accurately with the average range of minimal relative error between -6.67to 6.73% for temperature and -3.63 to 4.96% for moisture content measurements to both hard and soft wheat storages. The forecasted results were precisely done over 90% for most of the time. This justified that the model is capable of monitoring the climatic conditions of the storage for safe and future use of wheat grains, therefore the proposed model is recommended for the implementation in real time environment.
The storage condition measurement of grain crops is almost non-invasive to date; most of the technologies can be used to monitor the storage. Electromagnetic radiation is still popular wireless technique for grain storage condition management. It has led to the way of exploring safe methods for grain storage. The studies have shown that data detection using electromagnetic techniques has been attempted from various stances such as invasive and non-invasive approaches. Most of the existing methods utilize some form of dielectric techniques. Despite the current development, there is an increasing need for monitoring large amount of stored grains. The trend indicates the grain spoilage due to the inefficiency of detecting the climate parameters such as temperature and moisture content from storage of large amount of grains. The aim of this work is to propose the method capable of monitoring the storage facility with large amount of grains through wireless communication technology. It took into account the dielectric and radio refractive quantity properties of grains, and storage prediction based on hidden Markov for the elegant monitoring of the stored grains. The model was designed and implemented based on ZigBee technology for remote communication, where wheat is considered as the prime cereal grains for storage in large quantity. It is also tested based on the robustness, accuracy and precision to confirm its viability in real time. The results showed that the proposed method is robust in response to the climatic changes in the storage and is capable of monitoring the storage condition accurately with the average range of minimal relative error between -6.67to 6.73% for temperature and -3.63 to 4.96% for moisture content measurements to both hard and soft wheat storages. The forecasted results were precisely done over 90% for most of the time. This justified that the model is capable of monitoring the climatic conditions of the storage for safe and future use of wheat grains, therefore the proposed model is recommended for the implementation in real time environment.
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