Human Activity Pattern Prediction System for Smart Home Appliances

This paper proposes a model (HAPP) for learning and finding human action designs for Smart home applications based on huge amounts of data from smart homes. The proposed methodology quantifies and breaks down vitality use variations initiated by renters' behaviour using visit design mining, group research, and expectation. The HAPP System addresses the legal obligation to deconstruct energy consumption patterns at the machine level, which is directly linked to the actions of human. In the quantum/information cut of 24th, the information from shrewd meter is recursively mined, and the results are stored up throughout progressive mining works out. The HAPP System specifies the conditions for analysing the project that we use Keywords: Smart home, Data Mining, classifications, Human activity recognition

IoT-based Application of Information Security Triad

Information Security is the foremost concern for IoT (Internet of things) devices and applications. Since the advent of IoT, its applications and devices have experienced an exponential increase in numerous applications which are utilized. Nowadays we people are becoming smart because we started using smart devices like a smartwatch, smart TV, smart home appliances. These devices are part of the IoT devices. The IoT device differs widely in capacity storage, size, computational power, and supply of energy. With the rapid increase of IoT devices in different IoT fields, information security, and privacy are not addressed well. Most IoT devices having constraints in computational and operational capabilities are a threat to security and privacy, also prone to cyber-attacks. This study presents a CIA triad-based information security implementation for the four-layer architecture of the IoT devices. An overview of layer-wise threats to the IoT devices and finally suggest CIA triad-based security techniques for securing the IoT devices.

Intelligent Scheduling of Smart Home Appliances Based on Demand Response Considering the Cost and Peak-to-Average Ratio in Residential Homes

With recent developments, smart grids assured for residential customers the opportunity to schedule smart home appliances’ operation times to simultaneously reduce both the electricity bill and the PAR based on demand response, as well as increasing user comfort. It is clear that the multi-objective combinatorial optimization problem involves constraints and the consumer’s preferences, and the solution to the problem is a difficult task. There have been a limited number of investigations carried out so far to solve the indicated problems using metaheuristic techniques like particle swarm optimization, mixed-integer linear programming, and the grey wolf and crow search optimization algorithms, etc. Due to the on/off control of smart home appliances, binary-coded genetic algorithms seem to be a well-fitted approach to obtain an optimal solution. It can be said that the novelty of this work is to represent the on/off state of the smart home appliance with a binary string which undergoes crossover and mutation operations during the genetic process. Because special binary numbers represent interruptible and uninterruptible smart home appliances, new types of crossover and mutation were developed to find the most convenient solutions to the problem. Although there are a few works which were carried out using the genetic algorithms, the proposed approach is rather distinct from those employed in their work. The designed genetic software runs at least ten times, and the most fitting result is taken as the optimal solution to the indicated problem; in order to ensure the optimal result, the fitness against the generation is plotted in each run, whether it is converged or not. The simulation results are significantly encouraging and meaningful to residential customers and utilities for the achievement of the goal, and they are feasible for a wide-range applications of home energy management systems.

Research and application of K/S value in stain identification

Purpose The intelligent identification of stains can quickly and accurately identify stains. At present, stains are identified subjectively by appearance, color, taste, feel, location, etc. Color is an important factor in identifying stains. K/S value is used to analyze the color of textile fabric, and it has additivity. The purpose of the study is to explore its application in stain recognition is of great significance to intelligent washing. Design/methodology/approach A certain method used to stain the textile, then the K/S value of the textile before and after the stain was analyzed and tested by the color difference instrument. The K/S curve of the stain was calculated by the addition of K/S, and then the stain was identified and distinguished. Findings The K/S value of the textile stained with stains could be deducted by the K/S value of the color difference meter. After deducting the base cloth, the K/S curve of the same stain is basically the same. Then the stain can be identified and analyzed. Research limitations/implications The K/S value can be used for stain analysis, but it needs to be analyzed and tested in the laboratory. Practical implications This study provides a simple method for stains identification. Originality/value In addition to common methods of stain identification, such as appearance, color, feel, smell, location, stain removal materials, breaking the substrate, IR, etc., K/S value can be used for stain analysis. Identifying stains and washing them in a targeted way to achieve a better washing effect could provide certain technical support for the development of smart washing and smart home appliances.

Demand Response Requirements from the Cultural, Social, and Behavioral Perspectives

Demand-side response programs, commonly known as demand response (DR), are interesting ways to attract consumers’ participation to improve electric consumption patterns. Customers are encouraged to modify their usage patterns in reaction to price increases through DR programs. When wholesale market prices are high or network reliability is at risk, DR can help to establish a balance between electricity generation and consumption by providing incentives or considering penalties. The overall objective of adopting DR programs is to increase network reliability and decrease operational costs. Nevertheless, the successful deployment of DR programs requires a set of conditions without which no success can be guaranteed. Implementing DR programs and achieving customers’ optimal power consumption behavior could be obtained through technical methods, such as using smart home appliances and big data techniques. However, even if each of these approaches is correctly implemented, they are not able to address all aspects of the problem. The findings of several studies demonstrate that, in addition to technical and economic concerns, social, cultural, and behavioral variables play a significant role in DR implementation. Therefore, this paper investigated the social, cultural, and behavioral variables as critical requirements for implementing DR programs. Furthermore, a theoretical framework and an analytical model of the elements impacting the electricity consumption are introduced that should be considered by the planners.

Smart Architecture Energy Management through Dynamic Bin-Packing Algorithms on Cloud

Smart Home Architecture is suitable for progressive and symmetric urbanization. Data being generated in smart home appliances using internet of things should be stored in cloud where computing resources can analyze the data and generate the decisive pattern within no time. This additional requirement of storage, majorly, comprising of unfiltered data escalates requirement of host machines which carries with itself extra overhead of energy consumption; thus, extra cost has to be beard by service providers. Various static algorithms are already proposed to improve energy management of cloud data centers by reducing number of active bins. These algorithms are not able to cater to the needs of present heterogeneous requests generated in cloud machines by people of diversified work environment with adhering to the requirements of quality parameters. Therefore, the paper has proposed and implemented dynamic bin-packing approaches for smart architecture that can significantly reduce energy consumption without compromising upon makespan, resource utilization and Quality of Service (QoS) parameters. The novelty of the proposed dynamic approaches in comparison to the existing static approaches is that the proposed approach dynamically creates and dissolves virtual machines as per incoming and completed requests which is a dire need of present computing paradigms via attachment of time-frame with each virtual machine. The simulations have been performed on JAVA platform and dynamic energy utilized-best fit decreasing bin packing technique has produced better results in maximum runs.

Power analysis of smart home appliances based on SSA-TCN

The popularity of smart home equipment has led to higher requirements for equipment automation operation and maintenance. However, the energy consumption status and hidden faults of household equipment cannot be controlled in time only by using traditional monitoring methods. Therefore, this paper proposes a methods of power analysis for smart home appliances based on SSA-TCN using the energy consumption data of smart home appliances. The effective information of the data is extracted through the SSA singular spectrum analysis method, and the data sequence is input into the sequential convolutional network for judgment, so that the energy consumption status and working status of the equipment is obtained. The actual data is used as the training set and the test set to verify the recognition rate of the model. The experimental results show that the recognition rate of the method is about 82%, which provides an effective way for equipment automation and intelligent operation and maintenance.

Peran Interaksi Simbolik Dalam Perencanaan Komunikasi Pemasaran ( Studi Kasus Strogen Indonesia )

In the midst of the rise of communication through digital media and the internet, it is easier to disseminate information, so many companies use the internet as a means of marketing communication. One brand that uses the Internet as a marketing communication medium is Strogen Indonesia. Strogen is a private company that focuses on selling smart home appliances products that are present with the latest technology and have the aim of helping users do their daily homework. In carrying out marketing communications, Strogen Indonesia focuses on sharing attractive visuals of its products as a symbol that can be widely accepted by consumers. Strogen Indonesia shares the visuals of its products through various media such as company websites, Instagram, to Youtube. In addition, Strogen Indonesia also tries to listen to consumers and makes it easier for consumers to communicate by having various social media that actively answer various questions and complaints from customers to achieve the best customer service. Researchers want to focus on the title of the thesis "The Role of Symbolic Interaction in Marketing Communication Planning (Case Study of Indonesian Strogen)". This research uses symbolic interaction communication theory and marketing communication planning. For this research method using a qualitative approach with type one case study method. The research object is Strogen marketing communication planning activity while the research subjects are employees and employees who carry out Strogen Indonesia marketing communication planning activities. The method of data analysis was done through reduction, grouping and drawing conclusions.Di tengah maraknya komunikasi melalui media digital dan internet membuat semakin mudahnya penyebaran informasi maka banyak perusahaan menggunakan media internet ini sebagai suatu sarana komunikasi pemasaran. Salah satu brand yang menggunakan Internet sebagai media komunikasi pemasarannya adalah Strogen Indonesia. Strogen merupakan salah satu perusahaan swasta yang berfokus pada penjualan produk – produk smart home appliances yang hadir mengusung teknologi terbaru dan memiliki tujuan untuk membantu penggunanya dalam melakukan pekerjaan rumah sehari – hari. Dalam menjalankan komunikasi pemasaran, Strogen Indonesia berfokus membagikan visual yang menarik dari produk – produknya sebagai suatu simbol yang bisa diterima konsumen secara luas. Strogen Indonesia membagikan visual – visual dari produknya melalui berbagai macam media seperti situs perusahaan, Instagram, hingga Youtube. Selain itu Strogen Indonesia juga berusaha mendengarkan konsumen serta memudahkan konsumennya untuk berkomunikasi dengan memiliki berbagai media sosial yang aktif menjawab berbagai pertanyaan dan keluhan dari pelanggan untuk mencapai pelayanan pelanggan yang terbaik. peneliti ingin befokus pada judul skripsi “Peran Interaksi Simbolik Dalam Perencanaan Komunikasi Pemasaran (Studi Kasus Strogen Indonesia)”. Penelitian ini menggunakan teori komunikasi interaksi simbolik dan perencanaan komunikasi pemasaran. Untuk metode penelitian ini menggunakan pendekatan kualitatif dengan metode studi kasus tipe satu. Untuk Objek penelitian adalah kegiatan perencanaan komunikasi pemasaran Strogen sementara untuk subjek penelitian adalah karyawan dan karyawati yang melakukan kegiatan perencanaan komunikasi pemasaran Strogen Indonesia. Metode analisis data dilakukan melalui reduksi, pengelompokkan dan penarikan kesimpulan.