Data Management in IoT based Food Safety Monitoring system
Jakonen, Kaisa (2016-12-14)
Data Management in IoT based Food Safety Monitoring system
Jakonen, Kaisa
(14.12.2016)
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Turun yliopisto
Kuvaus
Siirretty Doriasta
Tiivistelmä
The Internet of Things (IoT) is a new application area in the industry which enable communication between devices and users, and to connect “Things” to the Internet. The IoT is the network of physical objects like devices, vehicles, sensors and wireless modems that are connected to a single device. IoT enables these objects to collect a large amount of data when the efficient data management is necessary. In industry, IoT based applications can be used in several areas, such as cities, home, transportation, logistics, healthcare, food tracking and safety. This thesis focuses on the industry area of food safety monitoring.
Data management in IoT is one of the most important things in food safety monitoring because data is collected from several different sensors. In addition to this, data management must be really efficient and straightforward thus enabling the quality of food safety. Data pre-processing, data fusion and decision making can be utilized to make data management as effective as possible. In pre-processing, data can be cleaned, integrated, transformed and reduced if needed. When data is pre-processed before data fusion and decision making, the information is reliable and the quality of food can be secured. Data fusion combines all the collected data to only one piece of information. This helps to choose the best solution among different degrees of food spoilage in decision making process. This all enables an efficient data management for food monitoring thus the quality of food monitoring is continuous in real-time.
The main purpose of this thesis is to design an efficient data management model for data fusion and decision making for food safety monitoring. Those models enable real-time communication and continuous data collection from the food products. Data fusion model enables to combine all the collected data from several different sensors to a one data item. A decision making process is based on the result of data fusion which includes information of food spoilage. Decision making model enables efficient decision making among three different cases based on knowledge of food spoilage. When a decision is made, the information can be sent forward to a user. Food will be safer and able to reduce the high food wastage.
Data management in IoT is one of the most important things in food safety monitoring because data is collected from several different sensors. In addition to this, data management must be really efficient and straightforward thus enabling the quality of food safety. Data pre-processing, data fusion and decision making can be utilized to make data management as effective as possible. In pre-processing, data can be cleaned, integrated, transformed and reduced if needed. When data is pre-processed before data fusion and decision making, the information is reliable and the quality of food can be secured. Data fusion combines all the collected data to only one piece of information. This helps to choose the best solution among different degrees of food spoilage in decision making process. This all enables an efficient data management for food monitoring thus the quality of food monitoring is continuous in real-time.
The main purpose of this thesis is to design an efficient data management model for data fusion and decision making for food safety monitoring. Those models enable real-time communication and continuous data collection from the food products. Data fusion model enables to combine all the collected data from several different sensors to a one data item. A decision making process is based on the result of data fusion which includes information of food spoilage. Decision making model enables efficient decision making among three different cases based on knowledge of food spoilage. When a decision is made, the information can be sent forward to a user. Food will be safer and able to reduce the high food wastage.