Intelligent Smart Home Energy Efficiency Model Using Artificial Intelligence and Internet of Things

Abstract In the path to sustainable development, it is very necessary to use technology in the right way. Today's world involves the usage of various energy-efficient devices in our day-to-day lives that leads to optimal utilization of energy. In this research work, the design and implementation of a smart home system model is proposed that can control all the electrical equipment as well as monitor the usage of every device being used in the smart home. The system will use the combination of artificial intelligence and Internet of Things technologies. This system will be useful for all individuals in their daily life to find comfort. The system not only optimizes the energy usage, but instead it also stands by the emergence of equipment that makes it a complete smart home package. The proposed system will monitor all the inputs and outputs throughout the house. These inputs and outputs may be a person, electricity, or water supply. This system will help in improving the current standard of living by monitoring these inputs. The water monitoring system will monitor the quality of water and its resources. These resources may be the groundwater or the treated water from rainwater harvesting. Similarly, it can be used even after the resources have been depleted; for example, the proposed system has to work for fulfilling today’s requirement of renewable sources of energy. This is done by using artificial intelligence in the system that will calculate the usage, and according to it, the system will switch to a hybrid mode that will use the solar energy and store extra charge in the battery.

[1]  Yuanqing Li,et al.  An EOG-Based Human–Machine Interface to Control a Smart Home Environment for Patients With Severe Spinal Cord Injuries , 2019, IEEE Transactions on Biomedical Engineering.

[2]  Mouna Rekik,et al.  Double layer home energy supervision strategies based on demand response and plug-in electric vehicle control for flattening power load curves in a smart grid , 2019 .

[3]  Savvas Papagiannidis,et al.  A systematic review of the smart home literature: A user perspective , 2019, Technological Forecasting and Social Change.

[4]  T. Logenthiran,et al.  Intelligent multi-agent system for smart home energy management , 2015, 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA).

[5]  Omar Hamdan,et al.  IoT-Based Interactive Dual Mode Smart Home Automation , 2019, 2019 IEEE International Conference on Consumer Electronics (ICCE).

[6]  Antonella Molinaro,et al.  On the Integration of Information Centric Networking and Fog Computing for Smart Home Services , 2019, The Internet of Things for Smart Urban Ecosystems.

[7]  Titouan Parcollet,et al.  The Pytorch-kaldi Speech Recognition Toolkit , 2018, ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[8]  Hidekazu Suzuki,et al.  Implementation of Secure End-to-End Remote Control System for Smart Home Appliances on Android , 2019, 2019 IEEE International Conference on Consumer Electronics (ICCE).

[9]  Kanisius Karyono,et al.  Smart fridge design using NodeMCU and home server based on Raspberry Pi 3 , 2017, 2017 4th International Conference on New Media Studies (CONMEDIA).

[10]  Adarsh Krishnamurthy,et al.  NURBS-Python: An open-source object-oriented NURBS modeling framework in Python , 2019, SoftwareX.

[11]  Dae-Man Han,et al.  Smart home energy management system using IEEE 802.15.4 and zigbee , 2010, IEEE Transactions on Consumer Electronics.

[12]  Imran A. Zualkernan,et al.  A smart home energy management system using IoT and big data analytics approach , 2017, IEEE Transactions on Consumer Electronics.

[13]  Carlo Fischione,et al.  Latency Analysis of Wireless Networks for Proximity Services in Smart Home and Building Automation: The Case of Thread , 2019, IEEE Access.

[14]  Christos Douligeris,et al.  ForChaos: Real Time Application DDoS Detection Using Forecasting and Chaos Theory in Smart Home IoT Network , 2019, Wirel. Commun. Mob. Comput..

[15]  Huimin Lu,et al.  Brain Intelligence: Go beyond Artificial Intelligence , 2017, Mobile Networks and Applications.

[16]  Marcel Fajkus,et al.  Smart Home room's occupancy monitoring using Fiber Bragg grating sensor , 2019, Optics + Optoelectronics.

[17]  Asif Qumer Gill,et al.  Privacy of IoT-Enabled Smart Home Systems , 2019 .

[18]  Neil W. Bergmann,et al.  IoT Privacy and Security Challenges for Smart Home Environments , 2016, Inf..

[19]  Fatih Erden,et al.  Sensors in Assisted Living: A survey of signal and image processing methods , 2016, IEEE Signal Processing Magazine.

[20]  Wei Chen,et al.  Smart Home: Architecture, Technologies and Systems , 2018 .

[21]  Diane J. Cook,et al.  Robot-enabled support of daily activities in smart home environments , 2019, Cognitive Systems Research.

[22]  Hamidreza Damghani,et al.  Smart home energy management, using IoT system , 2019, 2019 5th Conference on Knowledge Based Engineering and Innovation (KBEI).

[23]  Pradeepta Mishra Introduction to PyTorch, Tensors, and Tensor Operations , 2019 .

[24]  Tom Hargreaves,et al.  Learning to live in a smart home , 2018 .

[25]  M. S. Meghana,et al.  Real Time Iot Based Office Automation System Using Nodemcu Esp8266 Module , 2019 .

[26]  Xiaofeng Yin,et al.  Stochastic Optimal Energy Management of Smart Home With PEV Energy Storage , 2018, IEEE Transactions on Smart Grid.

[27]  Anju Sharma,et al.  Analysis of Load Balancing Algorithms using Cloud Analyst , 2016 .

[28]  Er. Ashima Pansotra,et al.  Cloud Security Algorithms , 2015 .

[29]  Vicente Julián,et al.  Designing a goal-oriented smart-home environment , 2016, Information Systems Frontiers.

[30]  Zhen Zhang,et al.  Wireless Power Transfer for Smart Industrial and Home Applications , 2019, IEEE Trans. Ind. Electron..

[31]  John Salvatier,et al.  Theano: A Python framework for fast computation of mathematical expressions , 2016, ArXiv.

[32]  Xiaohui Peng,et al.  Deep Learning for Sensor-based Activity Recognition: A Survey , 2017, Pattern Recognit. Lett..

[33]  Finn Arup Nielsen,et al.  Data Mining with Python (Working draft) , 2015 .

[34]  Jonathan Malmaud,et al.  TensorFlow.jl: An Idiomatic Julia Front End for TensorFlow , 2018, J. Open Source Softw..

[35]  Kazem Zare,et al.  Robust thermal and electrical management of smart home using information gap decision theory , 2018 .

[36]  R. Nagarajan,et al.  Brushless DC Motor Controlled by using Internet of Things , 2017 .

[37]  Tin Kam Ho,et al.  Machine Learning Made Easy: A Review of Scikit-learn Package in Python Programming Language , 2019, Journal of Educational and Behavioral Statistics.

[38]  Praveen Gauravaram,et al.  Blockchain for IoT security and privacy: The case study of a smart home , 2017, 2017 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops).

[39]  Adnan M. Abu-Mahfouz,et al.  Smart water meter system for user-centric consumption measurement , 2015, 2015 IEEE 13th International Conference on Industrial Informatics (INDIN).

[40]  Raman Maini,et al.  COMPARISON OF DATA ENCRYPTION ALGORITHMS , 2011 .

[41]  Ilhami Colak,et al.  Main Barriers and Solution Proposals for Communication Networks and Information Security in Smart Grids , 2018, 2018 International Conference on Smart Grid (icSmartGrid).

[42]  Ahmad Almogren,et al.  A robust human activity recognition system using smartphone sensors and deep learning , 2018, Future Gener. Comput. Syst..

[43]  Ke Xu,et al.  Toward software defined smart home , 2016, IEEE Communications Magazine.

[44]  Jean-Yves Fourniols,et al.  An Overview of Basics Speech Recognition and Autonomous Approach for Smart Home IOT Low Power Devices , 2018 .

[45]  Leandro A. Villas,et al.  Energy-efficient smart home systems: Infrastructure and decision-making process , 2019, Internet Things.

[46]  Suat Özdemir,et al.  A fog computing based smart grid model , 2016, 2016 International Symposium on Networks, Computers and Communications (ISNCC).

[47]  Nikhil Ketkar,et al.  Introduction to PyTorch , 2021, Deep Learning with Python.

[48]  Rita Yi Man Li,et al.  Sustainable Smart Home and Home Automation: Big Data Analytics Approach , 2016 .

[49]  B. B. Zaidan,et al.  Smart Home-based IoT for Real-time and Secure Remote Health Monitoring of Triage and Priority System using Body Sensors: Multi-driven Systematic Review , 2019, Journal of Medical Systems.

[50]  Zhi-Hong Mao,et al.  Human-Centered, Ergonomic Wearable Device with Computer Vision Augmented Intelligence for VR Multimodal Human-Smart Home Object Interaction , 2019, 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[51]  B. Reeder,et al.  Older women’s perceptions of wearable and smart home activity sensors , 2020, Informatics for health & social care.

[52]  Manisa Pipattanasomporn,et al.  Demonstration of a home energy management system with smart thermostat control , 2013, 2013 IEEE PES Innovative Smart Grid Technologies Conference (ISGT).

[53]  A. Kalam,et al.  Electric Vehicle (EV) in Home Energy Management to Reduce Daily Electricity Costs of Residential Customer , 2018 .

[54]  Neeti Gupta,et al.  Taking MQTT and NodeMcu to IOT: Communication in Internet of Things , 2018 .

[55]  Lei Zhao,et al.  Routing for Crowd Management in Smart Cities: A Deep Reinforcement Learning Perspective , 2019, IEEE Communications Magazine.

[56]  Rajesh Kumar,et al.  Fog computing: from architecture to edge computing and big data processing , 2018, The Journal of Supercomputing.

[57]  Sarah C. Darby,et al.  Smart technology in the home: time for more clarity , 2018 .

[58]  Trio Adiono,et al.  Efficient Android Software Development Using MIT App Inventor 2 for Bluetooth-Based Smart Home , 2019, Wirel. Pers. Commun..

[59]  Ian Cleland,et al.  Design and assessment of the data analysis process for a wrist-worn smart object to detect atomic activities in the smart home , 2019, Pervasive Mob. Comput..

[60]  Archie C. Chapman,et al.  A Fast Technique for Smart Home Management: ADP With Temporal Difference Learning , 2018, IEEE Transactions on Smart Grid.

[61]  Edris Pouresmaeil,et al.  A Centralized Smart Decision-Making Hierarchical Interactive Architecture for Multiple Home Microgrids in Retail Electricity Market , 2018, Energies.

[62]  Jan A. Snyman,et al.  PRACTICAL COMPUTATIONAL OPTIMIZATION USING PYTHON , 2018 .

[63]  Hongbo Zhu,et al.  Real-time pricing considering different type of smart home appliances based on Markov decision process , 2019, International Journal of Electrical Power & Energy Systems.

[64]  Ahmad Jalal,et al.  A Triaxial Acceleration-based Human Motion Detection for Ambient Smart Home System , 2019, 2019 16th International Bhurban Conference on Applied Sciences and Technology (IBCAST).

[65]  Ying Zhang,et al.  A Knowledge-Based Approach for Multiagent Collaboration in Smart Home: From Activity Recognition to Guidance Service , 2020, IEEE Transactions on Instrumentation and Measurement.

[66]  N. Krishna Prakash,et al.  Smart Home Energy Management System—A Multicore Approach , 2018, International Conference on Advanced Computing Networking and Informatics.

[67]  Reinhold Haeb-Umbach,et al.  NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing , 2018, ITG Symposium on Speech Communication.

[68]  Luigi Atzori,et al.  Smart Home Energy Management Including Renewable Sources: A QoE-Driven Approach , 2018, IEEE Transactions on Smart Grid.

[69]  Prashant J. Shenoy,et al.  SmartCharge: Cutting the electricity bill in smart homes with energy storage , 2012, 2012 Third International Conference on Future Systems: Where Energy, Computing and Communication Meet (e-Energy).

[70]  Rozita Teymourzadeh,et al.  Smart GSM based Home Automation System , 2013, 2013 IEEE Conference on Systems, Process & Control (ICSPC).

[71]  Nalini Venkatasubramanian,et al.  Smart Home Survey on Security and Privacy , 2019, ArXiv.

[72]  Alexis Boukouvalas,et al.  GPflow: A Gaussian Process Library using TensorFlow , 2016, J. Mach. Learn. Res..

[73]  Jian Shen,et al.  Secure data uploading scheme for a smart home system , 2018, Inf. Sci..

[74]  James E. Conaway Mr.,et al.  Pico Grid-Smart Home Energy Management System , 2019 .

[75]  M. Porter,et al.  How Smart, Connected Products Are Transforming Companies , 2015 .

[76]  Lukman Adewale Ajao,et al.  Project-Based Microcontroller System Laboratory Using BK300 Development Board With PIC16F887 Chip , 2015 .

[77]  Okba Kazar,et al.  New approach using an IoT robot to oversight the smart home environment , 2019 .

[78]  Andreas Jacobsson,et al.  A risk analysis of a smart home automation system , 2016, Future Gener. Comput. Syst..

[79]  Arne Berger,et al.  Sensing Home: Participatory Exploration of Smart Sensors in the Home , 2018, Social Internet of Things.