A Smart Home Energy Monitoring System Based on Internet of Things and Inter Planetary File System for Secure Data Sharing

Energy demand will continue to rise as a result of predicted population growth. In this work, a user-friendly home energy monitoring system based on IoT is described, which is capable of collecting, analyzing, and displaying data. Users register their sensors and devices on the monitoring platform. PostgreSQL and Elasticsearch databases are used to store the resulting measurements. In a smart home, the wireless sensor ACS712 was used to monitor the flow of electricity (current and voltage) for a household device. The user can share data about electricity consumption and costs with a third party via the private IPFS (InterPlanetary File System) network. A third party can download all the energy consumption data for a device or many devices from the platform for 1 day, 3 months, 6 months, and 1 year. The studies on the development of energy-efficient technology for home devices benefit greatly from the gathered data. For security in the system, it is preferred to run Keyrock Idm, Wilma Pep Proxy, and Orion Context Broker in HTTPS mode, and MQTTS is used to retrieve sensor data. The experimental results showed that the energy monitoring system accurately records voltage, current, active power, and the total amount of power used and offers low-cost solutions to the users using household devices in a day.

A Solution-Based Analysis of Attack Vectors on Smart Home Systems

The development and wider adoption of smart home technology also created an increased requirement for safe and secure smart home environments with guaranteed privacy constraints. In this paper, a short survey of privacy and security in the more broad smart-world context is first presented. The main contribution is then to analyze and rank attack vectors or entry points into a smart home system and propose solutions to remedy or diminish the risk of compromised security or privacy. Further, the usability impacts resulting from the proposed solutions are evaluated. The smart home system used for the analysis in this paper is a digital- STROM installation, a home-automation solution that is quickly gaining popularity in central Europe, the findings, however, aim to be as solution independent as possible.

A Novel User Behavior Prediction Model Based on Automatic Annotated Behavior Recognition in Smart Home Systems

User behavior prediction has become a core element to Internet of Things(IoT)and received promising attention in the related fields.Many existing IoT systems(e.g.smart home systems)have been deployed various sensors and the user’s behavior can be predicted through the sensor data.However,most of the existing sensor-based systems use the annotated behavior data which requires human intervention to achieve the behavior prediction.Therefore,it is a challenge to provide an automatic behavior prediction model based on the original sensor data.To solve the problem,this paper proposed a novel automatic annotated user behavior prediction(AAUBP)model.The proposed AAUBP model combined the Discontinuous Solving Order Sequence Mining(DVSM)behavior recognition model and behavior prediction model based on the Long Short Term Memory(LSTM)network.To evaluate the model,we performed several experiments on a real-world dataset tuning the parameters.The results showed that the AAUBP model can effectively recognize behaviors and had a good performance for behavior prediction.

Analysis Markov Delay Control Strategy for Smart Home Systems

with the development of science and technology, smart home systems require better, faster to meet the needs of human. In order to achieve this goal, the human-machine-items all need to interact each other with understand, efficient and speedy. Cps could unify combination with the human-machine-items; realize the interaction between the physical nformation and the cyber world. However, information interaction and the control task needs to be completed in a valid time. Therefore, the transform delay control strategy becomes more and more important. This paper analysis Markov delay control strategy for smart home systems, which might help the system decrease the transmission delay.

A Hybrid Intrusion Detection System for Smart Home Security Based on Machine Learning and User Behavior

With technology constantly becoming present in people’s lives, smart homes are increasing in popularity. A smart home system controls lighting, temperature, security camera systems, and appliances. These devices and sensors are connected to the internet, and these devices can easily become the target of attacks. To mitigate the risk of using smart home devices, the security and privacy thereof must be artificially smart so they can adapt based on user behavior and environments. The security and privacy systems must accurately analyze all actions and predict future actions to protect the smart home system. We propose a Hybrid Intrusion Detection (HID) system using machine learning algorithms, including random forest, X gboost, decision tree, K -nearest neighbors, and misuse detection technique.

A New Behavior-Assisted Semantic Recognition Method for Smart Home

In the recent Smart Home(SH)research work,intelligent service recommendation technique based on behavior recognition,it has been extensively preferred by researchers.However,most current research uses the Semantic recognition to construct the user’s basic behavior model.This method is usually restricted by environmental factors,the way these models are built makes it impossible for them to dynamically match the services that might be provided in the user environment.To solve this problem,this paper proposes a Semantic behavior assistance(Semantic behavior assistance,SBA).By joining the semantic model on the intelligent gateway,building an SA model,in this way,a logical Internet networks for smart home is established.At the same time,a behavior assistant method based on SBA model is proposed,among them,the user environment-related entities,sensors,devices,and user-related knowledge models exist in the logical interconnection network of the SH system through the semantic model.In this paper,the data simulation experiment is carried out on the method.The experimental results show that the SBA model is better than the knowledge-based pre-defined model.

An OS for Internet of Everything:Early Experience from A Smart Home Prototype

The proliferation of the Internet of Everything(IoE) has pulled computing to the edge of the network, such as smart homes, autonomous vehicles, robots, and so on. The operating system as the manager of the computing resources, is also facing new challenges.For IoE systems and applications, an innovative operating system is missing to support services, collect data, and manage the things. However, IoE applications are all around us and increasingly becoming a necessity rather than a luxury. Therefore, it is important that the process of configuring and adding devices to the IoE is not a complex one. The ease of installation, operation, and maintenance of devices on the network unarguably plays an important role in the wide spread use of IoE devices in smart homes and everywhere else. In this paper, we propose Sofie, which is a smart operating system for the IoE. We also give the design of Sofie. Sofie can be implemented via different IoT systems, such as Home Assistant, openHAB, and so on. In order to implement Sofie to get some early experience, we leverage Home Assistant to build a prototype for the smart home. Our work shows that Sofie could be helpful for practitioners to better manage their IoE systems.

Design and Implementation of a Novel HomePlug-Based Solution for Low Cost and High Performance Smart Home Networking

As the smart home is the end-point power consumer, it is the major part to be controlled in a smart micro grid. There are so many challenges for implementing a smart home system in which the most important ones are the cost and simplicity of the implementation method. It is clear that the major share of the total cost is referred to the internal controlling system network; although there are too many methods proposed but still there is not any satisfying method at the consumers＇ point of view. In this paper, a novel solution for this demand is proposed, which not only minimizes the implementation cost, but also provides a high level of reliability and simplicity of operation; feasibility, extendibility, and flexibility are other leading properties of the design.

Cyber-Physical-Social System Between a Humanoid Robot and a Virtual Human Through a Shared Platform for Adaptive Agent Ecology

Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.

基于Home Assistant简易家电智能控制系统的设计

【目的】本研究基于开源的Home Assistan(t HA)智能家居平台,设计出门禁、照明、电视机、窗及窗帘等简易家电的智能控制系统,能有效解决当前智能家居系统存在的成本高、操作烦琐及其众多系统互联互通难的问题。【方法】该系统以AMR主控板为核心,以人脸识别、智能感应和用户界面(UI)为用户交互终端,实现人脸识别和自动感应来控制家居终端设备,也可通过手机APP、电脑界面系统来远程控制家电设备。【结果】该系统的设计方案可靠,容易设计与实现,具有成本低廉、交互性灵活和操作简便等特点。【结论】其对家电智能化管理及智能家居的推广具有一定的指导意义。

An Investigative Study for Smart Home Security: Issues, Challenges and Countermeasures

Home security should be a top concern for everyone who owns or rents a home. Moreover, safe and secure residential space is the necessity of every individual as most of the family members are working. The home is left unattended for most of the day-time and home invasion crimes are at its peak as constantly monitoring of the home is difficult. Another reason for the need of home safety is specifically when the elderly person is alone or the kids are with baby-sitter and servant. Home security system i.e. HomeOS is thus applicable and desirable for resident’s safety and convenience. This will be achieved by turning your home into a smart home by intelligent remote monitoring. Smart home comes into picture for the purpose of controlling and monitoring the home. It will give you peace of mind, as you can have a close watch and stay connected anytime, anywhere. But, is common man really concerned about home security? An investigative study was done by conducting a survey to get the inputs from different people from diverse backgrounds. The main motivation behind this survey was to make people aware of advanced HomeOS and analyze their need for security. This paper also studied the necessity of HomeOS investigative study in current situation where the home burglaries are rising at an exponential rate. In order to arrive at findings and conclusions, data were analyzed. The graphical method was employed to identify the relative significance of home security. From this analysis, we can infer that the cases of having kids and aged person at home or location of home contribute significantly to the need of advanced home security system. At the end, the proposed system model with its flow and the challenges faced while implementing home security systems are also discussed.

居家养老慢性病患者智慧医疗服务需求研究

目的探讨居家养老慢性病患者智慧医疗服务需求,并分析需求实现与用户满意度之间的关系。方法采用招募法选择长春市299例居家养老慢性病患者为研究对象,采用混合研究方法,通过一般资料调查、半结构式访谈了解居家养老慢性病患者自我管理现状及健康服务需求,运用卡诺模型进行需求分类和优先级排序,最后结合产品服务系统的设计方法,构建产品和服务一起交付的智慧医疗产品新模式。结果需求指标3、4、9归属为必备型需求,需求指标1、5、8归属为期望型需求,需求指标7、10、11、13、14归属为魅力型需求,需求指标2、6、12、15归属为无差异型需求。结论居家养老慢性病患者智慧医疗服务应在维持和完善必备、期望属性需求基础上,发展和创新魅力属性需求,客观分析和改良无差异需求,以提升居家养老慢性病患者智慧医疗产品用户体验和服务质量。

基于DEMATEL模型的智能家居系统设计研究

探究智能家居系统要素构成关系,提高智能家居系统设计的科学性和系统性。整理智能家居产品的主要分类及代表产品,运用决策实验室分析法(DEMATEL)对系统内部各要素的交互关系及因果影响程度进行分析,构建各要素象限分布图,生成要素分布表并总结各要素的作用定位。智能家居系统要素的影响关系明显区别于传统家居系统,各要素权重相对平均且具有较强的联系性,呈现出多层次的复杂系统构成关系。运用DEMATEL模型可以明确智能家居系统中各要素的工作逻辑和影响关系,针对研究结果提出未来智能家居系统的完善策略和设计原则,从而制订更加科学合理的智能家居系统配置方案,为智能家居系统设计实践提供理论依据和路径参考。

智能家电技术现状及展望

为了满足人们不断增长的对美好生活的追求,家电智能化和智能家居技术正在快速发展。智能家电正沿智能单品、智能场景,以及智慧家庭逐步完善和系统化。人—机—环境系统工程研究人、机、环境特性和人—机、人—环境、机—环境关系,以及人—机—环境系统总体性。近几年大模型、生成式人工智能、知识图谱等人工智能技术为本轮智能家电的技术升级提供了强有力的技术支撑。结合目前智能家电现状,总结了智能家电的技术发展史、产品和技术现状,并结合人工智能技术的发展,分析智能家电技术未来的发展趋势。

智能化技术在家庭园艺景观养护中的设计探索与应用研究

当今社会逐渐步入数字化社会,物联网智能技术的不断发展,使得产品设计逐渐趋于智能化。在信息化技术促进产业变革的时代背景下,家庭园艺作为景观设计下的分支,也逐渐呈现出智能化的发展趋势:家庭智能园艺作为物联网技术与景观的切入点存在潜在的市场需求;物联网技术与景观的结合得益于多种复合技术层面的支持;物联网技术在未来景观绿化管理上存在很大应用前景。以浙江省大学生职业生涯规划与创业大赛一等奖《“智园”——基于IoT技术的家庭智能养护系统》为案例,分析基于物联网技术的智能家庭园艺产品的设计研究,并总结智能景观产品的设计策略:以人为本原则、系统化原则、低耗能原则、生态性原则、原真性原则,进一步拓展依托物联网技术的家庭智能园艺辐射范围,以期为家庭园艺设备在园艺领域乃至城市景观领域的应用开拓新路径。

智能家居系统的发展趋势和应用分析

本文回顾了智能家居系统从诞生到成熟的发展历程,介绍了此系统在通讯协议和布线形式方面的演进过程,通过总结大量工程实践经验,提出从“有线”到“无线”、从“集中”到“分布”的技术路线发展规律,为建筑智能化设计领域的专业人员提供一定参考。

基于物联网技术的智能家居系统设计

论文旨在设计一套融合物联网技术的系统,实现对家庭环境信息的采集及家用设备的控制,同时也能满足检测人体生理指标、实时监测老年人等人群健康状况的需求,使家居环境与人体状态之间相互协调,形成稳定的闭环系统。

基于Wi-Fi控制的智能家居监控系统软硬件设计

随着互联网、人工智能的发展,智能设备变得越来越普及且强大,智能家居控制设备是最常见的智能设备之一,对人们生活水平的改善产生重要的影响。该文基于Wi-Fi控制设计智能家居控制系统,提出一种基于STM32芯片的智能家居监控系统,该方法采用Wi-Fi和智能手机相连,并将数据传送给云平台,进而对数据进行智能处理。在具体设计中,该文首先对系统总体方案进行明确,其次根据总体方案设计芯片、各功能模块等硬件系统,随后设计所需系统平台,开发手机APP,利用Wi-Fi将数据传递到云服务器上,最后利用手机APP进行远程监控,从而实现温度湿度监控、灯光自动控制、火灾报警等功能,为用户提供个性化的居家服务。

自动化技术在智能家居系统中的应用与实践

智能家居系统以其能够提高生活便利性和节能效果的特点,逐渐成为人们日常生活的组成部分。自动化技术作为实现智能家居系统核心功能的重要手段,在安全、能源管理、娱乐等方面的应用已经取得了显著进展。研究旨在探讨自动化技术在智能家居系统中的具体应用与实践,深入了解其对家庭生活的影响。研究发现,自动化技术在智能家居系统中广泛应用于安全监控、环境控制、能源管理和家庭娱乐等方面。通过智能传感器、语音识别、远程控制等技术手段的整合,智能家居系统能够实现对家庭设备的智能化管理,提高家庭生活的便利性。

基于脑电波监测智能睡眠按摩枕头系统设计

设计了一种智能睡眠按摩枕头系统,旨在为用户提供有力的睡眠保障。该系统由TGAM脑电波检测、温湿度控制、按摩控制、蓝牙、网络通信等模块组成,通过实时调控智能睡眠产品,实现高度智能化、全自动化流程,从放松到入睡一体化设计,使用户睡眠舒心。此外,该睡眠无忧APP还兼具睡眠分期算法,自动生成睡眠深度分析报告,为用户提供个性化睡眠计划,同时搭配AI智能聊天回答分析用户睡眠情况,帮助用户更科学地改善睡眠体验。