Nico Surantha

Bio: Nico Surantha is an academic researcher from Binus University. The author has contributed to research in topics: Computer science & Orthogonal frequency-division multiplexing. The author has an hindex of 6, co-authored 60 publications receiving 208 citations. Previous affiliations of Nico Surantha include Kyushu Institute of Technology.

Intelligent Monitoring and Controlling System for Hydroponics Precision Agriculture

Abstract: Hydroponics agriculture comes up as a solution to limited agricultural land that can lead to a decline in agricultural production capacity. In Hydroponics agriculture, there is a challenge of precision agriculture, especially for some sensitive plants, e.g., bok choy and lettuce. These kinds of plants need a precise amount of nutrient and water every time to grow ideally. Internet-of-Things (IoT) is a technology that enables regular monitoring of every aspect of human life. It can be a solution to monitor the water and nutrition needs of the plants periodically. In this paper, we propose a monitoring and controlling system for hydroponics precision agriculture based on the IoT concept and Fuzzy logic. IoT is utilized to enable regular monitoring of plants nutrition and water needs, while fuzzy logic is used to control the supply of nutrition and water to the plants. The experiment result shows that the proposed system can produce better growth for lettuce and bok choy plants in terms of the size of leaves.

Indoor Air Quality Monitoring and Controlling System based on IoT and Fuzzy Logic

Abstract: Air pollution is one of the biggest health challenges in the world. Indoor air pollution is 2-5 times larger than outdoors, but people still do not care about it. Currently, people open the window or use an exhaust fan to refresh the air condition inside the room. However, people sometimes are too busy to pay attention to the air quality inside the room. Therefore, automation is required to bring the air quality into the required level. This study discussed indoor air quality monitoring and controlling system that can monitor the air condition and control the air condition using an exhaust fan. This system used the IoT concept in conducting real-time monitoring of carbon dioxide and PM10. The proposed system has fuzzy controls that could adjust the working interval of exhaust fan automatically depends on the concentration of each pollutant. Experiment results show that the proposed system shows excellent performance in controlling indoor air quality in terms of pollutant concentrator, AQI, and processing time to remove the pollutants.

Internet of things for sleep quality monitoring system: A survey

Abstract: Sleep quality is an important factor for human physical and mental health, day-time performance, and safety. Sufficient sleep quality can reduce risk of chronic disease and mental depression. Sleep helps brain to work properly that can improve productivity and prevent accident because of falling asleep. In order to analyze the sleep quality, reliable continuous monitoring system is required. The emergence of internet-of-things technology has provided a promising opportunity to build a reliable sleep quality monitoring system by leveraging the rapid improvement of sensor and mobile technology. This paper presents the literature study about internet of things for sleep quality monitoring systems. The study is started from the review of sleep quality problem, the importance of sleep quality monitoring, the enabling internet of things technology, and the open issues in this field. Finally, our future research plan for sleep apnea monitoring is presented.

[서평]「Applied Cryptography」

Abstract: The objective of this paper is to give a comprehensive introduction to applied cryptography with an engineer or computer scientist in mind. The emphasis is on the knowledge needed to create practical systems which supports integrity, confidentiality, or authenticity. Topics covered includes an introduction to the concepts in cryptography, attacks against cryptographic systems, key use and handling, random bit generation, encryption modes, and message authentication codes. Recommendations on algorithms and further reading is given in the end of the paper. This paper should make the reader able to build, understand and evaluate system descriptions and designs based on the cryptographic components described in the paper.

PhysioBank

Abstract: PhysioBank是一个大型的逐渐扩增的生理学信号和相关数据的数字化记录文档。目前包含多参数的心肺、神经和其他生物医学信号，尤以心电图（ECG）为主。信号来自健康受试者和各种疾病的患者。涉及的疾病包括心脏猝死、充血性心力衰竭、癫痫、步态不稳、睡眠呼吸暂停和衰老等。

Sleep stage classification from heart-rate variability using long short-term memory neural networks

Abstract: Automated sleep stage classification using heart rate variability (HRV) may provide an ergonomic and low-cost alternative to gold standard polysomnography, creating possibilities for unobtrusive home-based sleep monitoring. Current methods however are limited in their ability to take into account long-term sleep architectural patterns. A long short-term memory (LSTM) network is proposed as a solution to model long-term cardiac sleep architecture information and validated on a comprehensive data set (292 participants, 584 nights, 541.214 annotated 30 s sleep segments) comprising a wide range of ages and pathological profiles, annotated according to the Rechtschaffen and Kales (R&K) annotation standard. It is shown that the model outperforms state-of-the-art approaches which were often limited to non-temporal or short-term recurrent classifiers. The model achieves a Cohen’s k of 0.61 ± 0.15 and accuracy of 77.00 ± 8.90% across the entire database. Further analysis revealed that the performance for individuals aged 50 years and older may decline. These results demonstrate the merit of deep temporal modelling using a diverse data set and advance the state-of-the-art for HRV-based sleep stage classification. Further research is warranted into individuals over the age of 50 as performance tends to worsen in this sub-population.