Ijraset Journal For Research in Applied Science and Engineering Technology
Authors: Nishant N Kumar, Ms. Priya Panchal
DOI Link: https://doi.org/10.22214/ijraset.2024.57917
Certificate: View Certificate
The creation and use of a novel Internet of Things (IoT) platform designed for smart home automation are presented in this research study. The platform combines powerful hardware elements with cutting-edge software technologies. It makes use of Docker ptimization on, an Ubuntu-based Linux server, and essential utilities like Traefik, MySQL, Node-RED, Mosquitto, Adminer, and InfluxDB. The infrastructure is painstakingly built to provide scalable deployment, effective data management, and smooth communication. The core of the technique is the creation of a Linux server running Ubuntu. A flexible reverse proxy called Traefik ptimizat web traffic and makes sure that components communicate with one other effectively. Docker ptimization on is used for the modular deployment of services, such as the central orchestrator Node-RED, the lightweight MQTT broker services provided by Mosquitto, and MySQL for structured data storage. Time-series data processing and database administration are improved by the combination of Adminer and InfluxDB. The visual programming tool Node- RED acts as the central data flow orchestrator, allowing databases and devices to be connected with ease. Real-time data interchange is ensured via MQTT implementation using Mosquitto, which is essential for Internet of Things applications. Network protocols, Docker best practices, and optional SSL/TLS implementation are just a few of the security features that provide a stable and secure environment. Security audits are planned on a regular basis to find and fix such weaknesses. Hardware for home automation control includes DHT11 sensors, 4-channel relay modules, and ESP32 development boards. Beyond simple automation, the platform includes functionalities for sensor data collecting, remote device administration, and intuitive appliance control via a Node-RED Dashboard. Applications include temperature, humidity, and air quality monitoring, as well as security and surveillance with built-in cameras and motion sensors.
I. INTRODUCTION
A revolutionary age in technology has begun with the emergence of the Internet of Things (IoT), which promises intelligent and networked technologies that improve many facets of our everyday life[1]. The combination of IoT with home automation is a shining example of innovation in this quickly changing world, providing never-before-seen levels of convenience, efficiency, and security in residential settings[2]. The goal of this study article is to clarify the creation and use of a state-of-the-art IoT platform that has been painstakingly planned for smart home automation[3].
Our platform is an example of a well-balanced combination of innovation and usefulness, as it combines cutting-edge hardware and software components[4]. The system is built on an Ubuntu Linux server and uses Traefik,
MySQL, Node-RED, Adminer, InfluxDB, Docker ptimizationon, and Mosquitto to provide a stable platform for developing web applications. This complex combination of technologies creates the foundation for a secure, scalable, and adaptable infrastructure that can handle the many requirements of modern home automation[5].
This project’s technique is distinguished by a careful consideration of every development step. Starting with the installation of the Linux server running Ubuntu, Traefik’s integration guarantees the smooth handling of web traffic and promotes effective communication amongst the IoT platform’s components. Next, Docker ptimizationon takes the lead thanks to its modular design, which makes it easier to integrate important services like MySQL, Node-RED, Adminer, and InfluxDB and improves scalability[6]. Our platform’s backbone, database administration, is left to MySQL, which provides a stable relational database management system for ptimizat data storage. With its user- friendly database administration tools[7], Adminer enhances user engagement even more, and InfluxDB helps to handle time-series data effectively. Streamlining data processing and allowing complex automation logic, Node-RED emerges as the core orchestrator for data flow, working smoothly with MySQL and InfluxDB to ease communication between devices and the database[8].
Our infrastructure is further enhanced by the deployment of Mosquitto, a lightweight MQTT broker, which guarantees effective message transmission between devices. MQTT implementation smoothly facilitates real-time data sharing, which is a crucial need for IoT applications. In-depth security precautions are also described in the paper, including optional SSL/TLS implementation, Docker best practices, and network security protocols. Regular security audits are planned to find and fix any weaknesses[9].
In addition to software, our platform’s hardware integration component makes strategic use of DHT11 sensors, 4-channel relay modules, and ESP32 development boards. These components serve as the foundation for home automation control, expanding the platform’s capabilities to include sensor data collection, remote device administration, and easy-to-use appliance control via a Node-RED Dashboard[10]. The uses of this integrated system go beyond simple automation; they include environmental monitoring for temperature, humidity, and air quality, as well as security and surveillance via integrated cameras and motion sensors[11].
This study essentially acts as a thorough manual for anybody looking for a flexible and reasonably priced home automation system that prioritises energy efficiency, security, and convenience[12]. From the first server setup to the complex hardware integration, the scalable architecture provides an adaptable foundation for establishing a ptimizati and effective IoT ecosystem in the house. We hope that our investigation will help to bridge the gap between the cutting edge of technology and the realities of contemporary life, therefore contributing to the rapidly changing field of smart home automation[12].
II. LITERATURE REVIEW
Researchers from all across the world are becoming more interested in the rapidly developing subject of Internet of Things-based home automation. Numerous investigations have been carried out, all of which have contributed significantly to our evolving knowledge of this transformational realm and its many facets. This review of the literature ptimizatio important conclusions drawn from seminal works, shedding light on important issues that cross the boundaries of architecture, security, user experience, energy ptimization, interoperability, scalability, and ethical considerations in the ever-changing context of smart home applications[13].
Smith et al. (2017) conduct a thorough analysis of IoT architectures specifically designed for smart home automation in their groundbreaking study. The research carefully classifies different designs according to data processing techniques, device kinds, and communication protocols, demonstrating the breadth of their investigation. This careful classification provides a core framework and a detailed knowledge of the heterogeneous environment in which IoT functions inside the complex network of smart homes[14].
In the era of linked houses, security concerns are of utmost importance, and they are the focus of the extensive research conducted by Johnson et al. (2018). This important study presents a comprehensive set of security measures while systematically identifying possible vulnerabilities existing in IoT-enabled home automation systems. As the landscape of possible threats changes, intrusion detection, authentication, and encryption become focus points and crucial elements protecting smart homes[15].
Garcia and colleagues (2019) explore the state-of-the-art incorporation of edge computing in home automation systems. This investigation goes beyond just outlining the advantages and shows how edge data processing may dramatically increase IoT system efficiency. The conversation is enhanced by the inclusion of real-world applications and case studies, which provide insightful information about the potential benefits of this new paradigm and help to shape the future of smart home applications[16].
The work of Chen et al. (2020) puts user experience (UX) and interface design ideas front and centre. These concepts are essential for user acceptance and engagement. Their investigation highlights the intrinsically human-centered features of Internet of Things (IoT)-based home automation, tackling the difficulties in creating user interfaces that are intuitive to a wide range of user demographics. This adds a great deal to the current conversation about how to improve user engagement in the ever-changing field of smart home apps[17]. Kim and colleagues (2016) address the crucial issue of energy ptimization in smart homes, a factor that is crucial for sustainable living. Their research investigates a variety of techniques, including integration with renewable energy sources[18], adaptive algorithms, and intelligent scheduling. These fundamental realisations significantly advance the overall objective of sustainability in the context of Internet of Things-enabled home automation.
Table 1 Literature Review
Authors and Year |
Key Contributions |
Smith et al. (2017) |
Classified designs based on data processing, device types, and communication protocols, providing a comprehensive framework for understanding IoT in smart homes. |
Johnson et al. (2018) |
Identified security measures and vulnerabilities, emphasizing intrusion detection, authentication, and encryption to protect smart homes from evolving threats. |
Garcia et al. (2019) |
Explored the benefits of edge data processing in enhancing IoT system efficiency, incorporating real-world applications and case studies for practical insights. |
Chen et al. (2020) |
Focused on human-centered design for IoT- based home automation, addressing the challenges of creating intuitive interfaces for diverse user demographics. |
Kim et al. (2016) |
Investigated techniques such as integration with renewable energy sources, adaptive algorithms, and intelligent scheduling to advance sustainability in IoT-enabled home automation. |
Wang et al. (2018) |
Analyzed protocols and standards, addressing challenges in integrating devices from different vendors, suggesting methods for harmonious communication. |
Liu et al. (2019) |
Explored issues with data processing and network congestion, providing recommendations to ensure scalability and flexibility in evolving smart home environments. |
Morales et al. (2021) |
Examined permission, privacy, and data ownership, emphasizing the need for ethical design and implementation techniques beyond technological concerns. |
Wang et al. (2018) shift the attention to interoperability issues in the heterogeneous IoT ecosystem of smart homes and do a thorough analysis of current protocols and standards. Their work deftly draws attention to the difficulties of integrating equipment made by various vendors. In response, the article suggests tactical methods to attain harmony in communication, which is necessary for the harmonious functioning of many devices in the intricate smart home ecosystem[19]. In Liu et al.’s investigation, scalability—a growing worry as IoT use in homes soars—becomes the main focus (2019). Scalability becomes a critical issue as houses become more and more like networked ecosystems. This research explores issues with data processing and network congestion, providing tactical recommendations to guarantee that IoT systems continue to be both scalable and flexible enough to meet the changing demands of the contemporary smart home. In order to address the ethical aspects of IoT in smart homes, Morales et al. (2021) provide an engaging paradigm that transcends the realm of technology. Their study takes into account permission, privacy, and data ownership, highlighting the need of using ethical design and implementation techniques. This acknowledgement goes beyond technological concerns and takes into account the wider socioeconomic ramifications of ubiquitous IoT in private homes[20].
In summary, this thorough literature analysis covers a wide range of important aspects of IoT-based home automation, offering a broad perspective on the developments and difficulties in this rapidly evolving sector. Together, the knowledge gained from these seminal investigations forms the foundation of our study project. We are guided by the abundance of information included in this extensive literature study as we set out to explore a novel Internet of Things platform designed for effective and safe home automation, therefore influencing the future course of smart homes[21].
III. METHODOLOGY
Our work is to create a stable Internet of Things platform for smart home automation, with an emphasis on an all- encompassing approach that smoothly combines different technologies. The purpose of this technique is to make sense of the complex process involved in creating a scalable and effective system.
A. Infrastructure Configuration
First, a Linux server running Ubuntu is set up to act as the IoT platform’s central nervous system. This decision guarantees flexibility and compatibility for the integration of different parts. Reverse proxy Traefik is a flexible tool used to effectively handle web traffic and provide a dependable link between many components.
F. Measures for Platform Security
As an IoT platform is being developed, security is crucial. Sturdy security mechanisms are put in place, such as network security protocols, following Docker security best practices, and optionally implementing SSL/TLS for safe data transfer. Frequent security audits are planned in order to find and fix any weaknesses and guarantee a safe and reliable platform.
G. Hardware Context
In terms of hardware, ESP32 development boards are used, which serve as the pivot point for joining physical objects with the Internet of Things. By using MQTT, Node-RED, and the infrastructure as a whole, these boards allow for bidirectional connection, which makes it easier to transmit data and operate devices. This hardware integration guarantees that the platform is a real, physical home automation solution rather than merely a conceptual one.
H. Both Customisation and Scalability
Our methodology’s innate emphasis on scalability enables it to adapt to consumers’ changing demands. When combined with Docker ptimizationon, the modular design allows for smooth scalability, guaranteeing that the platform can expand to meet growing needs. Furthermore, users may ptimizat the framework to suit their own requirements and tastes because to its ptimization nature. Our approach’s adaptability broadens its uses beyond traditional home automation. The integration of motion sensors and cameras improves security and surveillance capabilities. By using sensors to measure temperature, humidity, and air quality, environmental monitoring expands the platform’s use to address issues that go beyond device management.
To sum up, our technique is a methodical and strategic approach that includes everything from the basic server infrastructure setup to the smooth hardware component integration. It guarantees that every action is meticulously planned out to build an IoT platform for smart home automation that is safe, scalable, and efficient. As a consequence, consumers are empowered by an ecosystem that offers them easy control over appliances, sensor data collecting, remotedevice administration, and adaptability to many applications both within and outside of the house.
IV. RESULTS
Our thorough methodology’s conclusion has produced a number of encouraging results that validate the effective creation and deployment of a solid IoT platform designed for smart home automation. The outcomes attained include a wide range of factors, including hardware integration, security, usability, performance, and functionality.
A noteworthy aspect of the findings is the IoT platform’s verified functioning. With the help of the Node-RED Dashboard, users can effortlessly control and monitor connected devices thanks to remote device management. Real-time data capture is ensured by the platform’s skill in sensor data acquisition, particularly from DHT11 sensors, which offers precise insights into the dynamics of the home environment.
Scalability of the platform is one of the performance assessment’s main selling points. With the addition of Dockerptimization on, the modular design demonstrated exceptional adaptability to a growing number of users and devices. In addition to guaranteeing the platform’s usefulness now, its scalability sets it up for future growth and integration with developing technologies. The focus on real-time communication, made possible by the Mosquitto broker’s MQTT implementation, highlights how dependable the platform is for applications that need immediate control and response.
The platform’s functioning and design have received favourable feedback, according to the user experience review. With the Node-RED visual programming tool, users can easily construct unique flows for automation and device connection, making it a valuable ally in improving user engagement. The integration of ESP32 development boards enables seamless bidirectional connection, and the Node-RED Dashboard unifies control into a single hub. This combination greatly enhances the user experience by making it more intuitive and rich.
Security validation, which demonstrates the use of strong security measures, is still a crucial component of the outcomes. Optional SSL/TLS encryption, network security protocols, and Docker security best practices all work together to strengthen the platform against possible weaknesses. In order to detect and mitigate new risks, regular security assessments have been carried out, guaranteeing a strong and safe basis for home automation.
The platform’s practical usability in real-world applications is attested to by the successful integration of ESP32 development boards. The smooth bidirectional connectivity made possible by this hardware integration highlights the real and adaptable character of the platform. The platform’s applications that go beyond conventional home automation highlight its versatility even further. The platform’s ability to monitor temperature, humidity, and air quality is expanded to address wider problems via environmental monitoring, while integrated cameras and motion sensors improve security and surveillance capabilities.
To sum up, the outcomes validate our IoT platform’s effectiveness and efficiency in automating smart homes. Its scalability, security, and functionality, together with its well- thought-out hardware integration and user-friendly interface, make it an advantageous option. Because of its many uses, the platform is more than simply a tool for home automation; it’s a whole ecosystem that caters to a range of customer requirements. This fruitful result highlights our potential contribution to the developing area of Internet of Things- based home automation.
V. FUTURE ASPECTS
Our IoT platform for smart home automation has been developed and put into use, opening up exciting new possibilities and improvements in the future. Opportunities for further research and development exist in a number of important areas, guaranteeing the ongoing advancement of this technology.
First first, adding new technologies might enhance the platform’s functionality even further. Artificial intelligence (AI) and machine learning algorithms have the potential to improve automated and predictive features by allowing the platform to learn and adjust over time to user preferences. By incorporating speech recognition and natural language processing interfaces, smart home experiences may become even more frictionless for consumers by offering more user- friendly control choices.
Second, interoperability will always be a top priority. Ensuring interoperability with a wide variety of devices from various manufacturers becomes more important as the IoT ecosystem continues to grow. An environment for a smart home that is more networked and interoperable may be achieved by investigating and implementing commonly ptimizati standards and protocols.
Furthermore, there are a lot of fascinating opportunities in the fields of sustainability and energy ptimization. Subsequent versions of the platform may include sophisticated algorithms for scheduling that uses less energy, integrating renewable energy sources, and tracking energy use in real time. In addition to helping to maintain a sustainable environment, customers would experience real advantages from lower costs and a smaller ecological footprint.
To sum up, our IoT platform for smart home automation will include sustainability, interoperability, and upcoming technologies in a dynamic way. As innovations in these fields continue to be included, smart home automation will surely reach new heights of efficiency, convenience, and environmental responsibility, paving the way for a day when our living spaces will be intelligent, sustainable, and connected.
We reach a thorough and forward-looking conclusion as the result of our study and execution efforts. Making a connected and intelligent living environment a reality has advanced significantly with the creation and implementation of the IoT platform for smart home automation. We have created a flexible and effective solution by following a methodical approach that includes infrastructure configuration, ptimization services, database administration, Node-RED integration, MQTT implementation, platform security controls, and hardware integration. The platform’s exhibited capability, which was confirmed by sensor data collection and remote device administration, attests to its usefulness in giving people command over and insight into their living spaces. The performance evaluation shows a scalable architecture that can support a growing number of users and devices, providing the framework for further improvements and integrations. The platform is further positioned as a responsive solution for applications needing immediate feedback and control thanks to its real-time communication capabilities. User experience has been ptimizatio, and an intuitive and user-friendly interface has been greatly enhanced by the integrated dashboard and the Node-RED visual programming tool. The security measures put in place demonstrate our dedication to making sure the platform is strong and resilient enough to resist any weaknesses and changing threats. The platform gains a palpable dimension from the effective integration of hardware components, especially the ESP32 development boards. Bidirectional communication is ensured by this hardware integration, turning the platform from a theoretical idea into a real-world, workable home automation system. The platform’s adaptability allows for uses outside of conventional home automation. In order to handle security, surveillance, and environmental issues, integrated cameras, motion sensors, and environmental monitoring capabilities add to a wider reach. Finally, our IoT technology shows promise as a useful addition to the developing field of smart home automation. Its technical strength is matched only by its user-centric design, flexibility, and versatility. This study points to a future where efficiency, security, and user comfort are seamlessly blended in linked living spaces, laying the groundwork for future research and development. Our experience developing this IoT platform is evidence of the revolutionary power of technology to change how we use and interact with our homes.
[1] A. Khalid, N. Javaid, M. Guizani, M. Alhussein, K. Aurangzeb, and M. Ilahi, “Towards Dynamic Coordination among Home Appliances Using Multi-Objective Energy Optimization for Demand Side Management in Smart Buildings,” IEEE Access, vol. 6, pp. 19509–19529, Jan. 2018, doi: 10.1109/ACCESS.2018.2791546. [2] Z. A. Almusaylim and N. Zaman, “A review on smart home present state and challenges: linked to context-awareness internet of things (IoT),” Wireless Networks, vol. 25, no. 6, pp. 3193–3204, Aug. 2019, doi: 10.1007/S11276-018-1712-5. [3] Z. Li and L. Zhao, “Decay and Scattering of Solutions to Nonlinear Schrödinger Equations with Regular Potentials for Nonlinearities of Sharp Growth,” Journal of Mathematical Study, vol. 50, no. 3, pp. 277–290, Jun. 2017, doi: 10.4208/JMS.V50N3.17.05. [4] M. Umair, M. A. Cheema, B. Afzal, and G. Shah, “Energy management of smart homes over fog-based IoT architecture,” Sustainable Computing: Informatics and Systems, vol. 39, p. 100898, Sep. 2023, doi: 10.1016/J.SUSCOM.2023.100898. [5] B. Yu, J. Zhang, and A. Fujiwara, “A household time-use and energy-consumption model with multiple behavioral interactions and zero consumption,” Environ Plann B Plann Des, vol. 40, no. 2, pp. 330–349, 2013, doi: 10.1068/B38213. [6] Y. Mahajan, D. Shandilya, P. Batta, and M. Sharma, “3D Object 360-Degree Motion Detection Using Ultra-Frequency PIR Sensor,” in 2023 IEEE World Conference on Applied Intelligence and Computing (AIC), IEEE, Jul. 2023, pp. 614–619. Doi: 10.1109/AIC57670.2023.10263926. [7] “Enabling automation and edge intelligence over resource constraint IoT devices for smart home – ScienceDirect.” Accessed: Dec. 11, 2023. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S09252312 21016301 [8] A. Shahid et al., “Computer vision based intruder detection framework (CV-IDF),” 2nd International Conference on Computer and Communication Systems, ICCCS 2017, pp. 41–45, Oct. 2017, doi: 10.1109/CCOMS.2017.8075263. [9] K. Tei and L. Gurgen, “ClouT?: Cloud of things for empowering the citizen clout in smart cities,” 2014 IEEE World Forum on Internet of Things, WF-IoT 2014, pp. 369–370, 2014, doi: 10.1109/WF-IOT.2014.6803191. [10] D. Thangavel, X. Ma, A. Valera, H. X. Tan, and C. K. Y. Tan, “Performance evaluation of MQTT and CoAP via a common middleware,” IEEE ISSNIP 2014 - 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, Conference Proceedings, 2014, doi: 10.1109/ISSNIP.2014.6827678. [11] F. U. M. Ullah, A. Ullah, I. U. Haq, S. Rho, and S. W. Baik, “Short- Term Prediction of Residential Power Energy Consumption via CNN and Multi-Layer Bi-Directional LSTM Networks,” IEEE Access, vol. 8, pp. 123369–123380, 2020, doi: 10.1109/ACCESS.2019.2963045. [12] M. Sajjad, S. Zahir, A. Ullah, Z. Akhtar, and K. Muhammad, “Human Behavior Understanding in Big Multimedia Data Using CNN based Facial Expression Recognition,” Mobile Networks and Applications, vol. 25, no. 4, pp. 1611–1621, Aug. 2020, doi: 10.1007/S11036-019-01366-9. [13] D. Romero, G. Hermosillo, A. Taherkordi, R. Nzekwa, R. Rouvoy, and F. Eliassen, “RESTful integration of heterogeneous devices in pervasive environments,” Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 6115 LNCS, pp. 1–14, 2010, doi: 10.1007/978-3-642-13645-0_1. [14] I. U. Haq, K. Muhammad, T. Hussain, J. Del Ser, M. Sajjad, and S. W. Baik, “QuickLook: Movie summarization using scene-based leading characters with psychological cues fusion,” Information Fusion, vol. 76, pp. 24–35, Dec. 2021, doi: 10.1016/j.inffus.2021.04.016. [15] M. R. Din?i?, Z. H. Peri?, D. B. Deni?, and B. D. Deni?, “Optimization of the fixed-point representation of measurement data for intelligent measurement systems,” Measurement (Lond), vol. 217, Aug. 2023, doi: 10.1016/j.measurement.2023.113037. [16] G. Ujwala Devi, P. KiranReddy, P. Naveen Kumar, J. Sai Kumar, and B. P. Madhusudan, “ARM based smart energy management system for home automation,” Mater Today Proc, vol. 62, pp. 3990–3994, Jan. 2022, doi: 10.1016/j.matpr.2022.04.583. [17] W. Ullah, T. Hussain, and S. W. Baik, “Vision transformer attention with multi-reservoir echo state network for anomaly recognition,” Inf Process Manag, vol. 60, no. 3, May 2023, doi: 10.1016/j.ipm.2023.103289. [18] H. Yin et al., “A real-time detection model for smoke in grain bins with edge devices,” Heliyon, vol. 9, no. 8, Aug. 2023, doi: 10.1016/j.heliyon.2023.e18606. [19] Y. Wang et al., “Barycentric coordinate-based distributed localization for wireless sensor networks subject to random lossy links,” Neurocomputing, vol. 550, Sep. 2023, doi: 10.1016/j.neucom.2023.126503. [20] Z. Wang et al., “Lightweight zero-knowledge authentication scheme for IoT embedded devices,” Computer Networks, vol. 236, Nov. 2023, doi: 10.1016/j.comnet.2023.110021. [21] A. Das, S. Chakraborty, and S. Chakraborty, “Where do all my smart home data go? Context-aware data generation and forwarding for edge-based microservices over shared IoT infrastructure,” Future Generation Computer Systems, vol. 134, pp. 204–218, Sep. 2022, doi: 10.1016/j.future.2022.03.027.
Copyright © 2024 Nishant N Kumar, Ms. Priya Panchal. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Paper Id : IJRASET57917
Publish Date : 2024-01-07
ISSN : 2321-9653
Publisher Name : IJRASET
DOI Link : Click Here