Kanae Matsui

Proposal for home energy management system to survey individual thermal comfort range for HVAC control with little contribution from users

Heating, ventilation, and air conditioning (HVAC) control is used to effectively reduce energy consumption in a home energy management system (HEMS). For the HVAC control, it is necessary to evaluate the indoor comfort level because the HVAC operation is significantly related to indoor environmental conditions. Although there are some indices for indoor comfort, individuals have different comfort ranges. A questionnaire is one way to gather data on individual comfort ranges. However, it requires contributions from users. Therefore, we proposed a new survey method that varied the intervals of the questions addressed to users to reduce the number of responses needed. Additionally, a comfort estimation method was proposed that did not require a questionnaire. This method analyzes the users operation of the HVAC system, such as touching its on/off switch. An HEMS with the capability of utilizing these two methods was installed in a laboratory and 16 houses in Miyagi prefecture, Japan. An experiment using this HEMS was conducted, and it was able to reduce the number of feedbacks needed to maintain each persons comfort by an average of 32.2%. The HEMS provided the same accuracy as hourly questionnaires. Namely, it confirmed that the estimation based on the air conditioner operations was almost the same as that based on an hourly questionnaire.

A Proposal of Framework for Information Visualization in Developing of Web Application

In recent years, everybody can get many kinds of real-time digital information easily, especially by using API as an infrastructure system which provides information data sets via the Internet. This system has changed a style of spreading information on the Internet. In a case of web developers, they utilize the real-time data sets which are created per time set by providers to create the web applications. These applications provide real-time information for the users then the users can get real-time information from them simply. However, there is a problem. This situation means many web applications using same source leads the situation which the users have to see same information often. Spreading same information leads too much information which the users cannot find out the information they need. To solve these problems, we propose a framework using the method of information visualization. This framework has two functions also has a purpose to make an environment to create information visualized web applications easily. One of them is to extract only important information from the large amount of information for understanding its essence of meaning well. The other is to generate values for visual effects like size and color which could be used for user interface to encourage the users to understand informations essence quickly. Both function are processed in a data base. The data base provides data sets including important information and visual values as XML data format to web developers. Therefore, they only focus on how express information on the user interface. As a result, the users can get only meaningful information with visual effects. To evaluate this frameworks validity, we count how many processes are needed to make an information visualized web application with a ordinal way and the other way used our proposed frameworks data sets. This result count shows that the proposed framework has more success over the ordinal method.

Privacy-preserving data collection for demand response using self-organizing map

Homomorphic encryption for smart grids has been investigated in many studies. It is possible to estimate the total power consumption in an area without knowing the consumption data of individual households. In the case of demand response (DR), it is important to calculate the total electric power consumption in an area because DR reports are published accordingly to reduce peak power consumption when the demand is high. However, the published data may reveal private information about residents, such as the timings of specific activities (leaving from and returning home), and device details. To overcome this problem, we propose a method specialized to enable energy providers to securely share electric power consumption data. The proposed method uses a self-organizing map (SOM), which is an unsupervised learning method. In order to share power consumption data while preserving privacy, the SOM is shared without the raw data. In this framework, a target accuracy of nearly 3% is achieved, while actual data are not published by any company.

An information provision system to promote energy conservation and maintain indoor comfort in smart homes using sensed data by IoT sensors

Abstract Smart cities are often discussed in the context of promoting sustainability. A smart city operates using large numbers of networked sensors to collect, store, and analyze massive amounts of data in near-real time; these data may also have secondary applications. This study proposes one such use of the data gathered by home energy management systems (HEMS). Current HEMS focus mainly on energy efficiency, but residents typically value indoor comfort as well. HEMS collect various types of data that can be used to create an index for short-term indoor comfort called the predicted mean vote (PMV). This study implements a system to identify information within the stored data that is relevant to reducing electricity consumption while maintaining indoor comfort according to each resident’s PMV preference. The system was tested in three households in Japan for 12 days in winter. The system reduced electricity consumption by 5.15% and increased the comfort satisfaction expressed as PMV by 42.3%. Qualitative assessments of indoor comfort increased by 16.4%. Providing users with information selected according to their PMV preferences was more effective in reducing electricity consumption and increasing indoor comfort than providing them with random information.

RAM-based hardware accelerator for network data anonymization

Many network services including intrusion detection and recommendation provide their services by analyzing information acquired from network transactions. A careful analysis of these data can reveal valuable information when deep packet inspection is performed. Since these packet analyses generate sensitive information from enormous volumes of transmitted data, the requirement for data anonymization has been discussed. There have been many studies of anonymization techniques and their implementation in software applications. However, limited research has been undertaken regarding hardware-based anonymizers. This paper proposes and evaluates a RAM-based anonymization architecture that maintains both high throughput and a low information-loss ratio.

Cost-effective air conditioning control considering comfort level and user location

Heating, ventilation, and air conditioning (HVAC) are important factors for a building energy management system (BEMS). Efficient control of the air conditioning (AC) is required to maintain both energy efficiency and human comfort. However, AC control systems are expensive to install in buildings. In this study, a cost-effective AC control system intended for a library is proposed; it is also applicable to other facilities such as offices and meeting spaces. This system uses seating sensors for maintaining both energy efficiency and human comfort. Conventional AC control systems generally use expensive motion sensors or vision sensors as well as temperature and humidity sensors to acquire information on both the location and the comfort of users and to provide location-based control to users. In order to reduce sensor-based cost, the proposed system uses low-cost pressure sensors and maintains both energy efficiency and the comfort level. For detecting seat occupancy and locations, low-cost pressure sensors and low-power communication nodes are attached to chairs and they transmit seating data to the database of a server. A programmable logic controller is used to control the proposed AC system according to the information stored in the database. The system is evaluated using a 10-day experiment conducted at a library in Kurihara City in Miyagi prefecture of Japan. The results of energy efficiency evaluation in this experiment show that the proposed system can reduce electricity consumption by 18.3%. Through measurement of the predicted mean vote values of users of the library, the proposed system is found to be capable of maintaining user comfort.