Energy efficiency and renewable energy are the two main research topics for sustainable energy. In the past ten years, countries around the world have invested a lot of manpower into new energy research. However, in addition to new energy development, energy efficiency technologies need to be emphasized to promote production efficiency and reduce environmental pollution. In order to improve power production efficiency, an integrated solution regarding the issue of electric power load forecasting was proposed in this study. The solution proposed was to, in combination with persistence and search algorithms, establish a new integrated ultra-short-term electric power load forecasting method based on the adaptive-network-based fuzzy inference system (ANFIS) and back-propagation neural network (BPN), which can be applied in forecasting electric power load in Taiwan. The research methodology used in this paper was mainly to acquire and process the all-day electric power load data of Taiwan Power and execute preliminary forecasting values of the electric power load by applying ANFIS, BPN and persistence. The preliminary forecasting values of the electric power load obtained therefrom were called suboptimal solutions and finally the optimal weighted value was determined by applying a search algorithm through integrating the above three methods by weighting. In this paper, the optimal electric power load value was forecasted based on the weighted value obtained therefrom. It was proven through experimental results that the solution proposed in this paper can be used to accurately forecast electric power load, with a minimal error.
Automation systems are widely applied in many fields such as manufacturing, warehousing, machinery, power management, and smart living spaces. In this study, a bidirectional security system was designed and applied to intravenous (IV) infusion for wards in hospitals. The system comprised a high-resolution gravity sensor, a 2.4 GHz XBee wireless sensor network communication module, and a drip-quantity-detecting control box with a HOTEC Corp. MCU HT66F70A core microprocessor to achieve automated management in the medical field. Toward achieving sustainability in our medical environment and computer science technology, we adopted data transformation, an Internet of Things (IoT) wireless communication and sensor network, and an app to construct the bidirectional security system for IV infusion. The main aims of the proposed method in this study were as follows: (1) to invent a reliable method to detect the remaining quantity of a patient's drip infusion using a gravity sensor so as to prevent the dangerous condition of blood flowing backward or air intruding into the vein as well as to decrease the burden on nursing staff in wards, and (2) to avoid medical disputes due to the incorrect infusion from drips, the autorecognition of patients using scanning QR code technology was applied in the medical management system. The outcome of the study was proved successful and has won many important national invention contests.
Earthquakes often cause severe disasters. Taiwan is located in an earthquake zone, where earthquakes occur frequently. For example, the Meinong earthquake in Kaohsiung in 2016 and the Hualien earthquake in 2018 caused the collapse of buildings in Tainan and Hualien, resulting in a total of 232 deaths and more than 100 injuries. Due to the strong vibration, earthquakes are often accompanied by fire and the leakage of toxic gases, causing loss of life and property. In this study, we integrate Arduino, sensors, and transmission technology to design an earthquake detection and warning system. When an earthquake is detected, the system immediately notifies everyone to evacuate. When the harmful gas concentration exceeds a critical value, the warning light is switched on, and the exhaust fan is turned on to extract the indoor toxic gas. When the flame sensor detects a flame, the system activates an alarm to warn people to escape quickly. In the designed system, capacitive three-axis accelerators are used as vibration measurement sensors to issue warnings in the early stage of an earthquake. In addition, the system includes an IR flame sensor to detect fires and an MQ series air quality sensor to detect harmful gases. The newly designed sensing system not only has the advantage of notifying people immediately during an earthquake but is also cheap and easy to use.
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