Courant: Revolutionizing Power Management for MSMEs with IoT Integration and Predictive Maintenance using Isolation Forest and LSTM Algorithms

John Edmerson L. Pizarra
Kevern Joebert C. Angeles
Jian Ross G. Dela Rosa
Florence Gayle C. Magpoc

ABSTRACT

Courant: Revolutionizing Power Management for MSMEs with IoT Integration and Predictive Maintenance using Isolation Forest and LSTM Algorithms is a progressive web application that monitors power consumption and provides data-driven insights to MSME owners. Designed to improve efficiency, reduce costs, and prevent equipment damage, it features remote device management, real-time alerts, and AI-powered predictive maintenance. Courant operates with EDMER devices, IoT hardware where appliances are connected to measure consumption and detect anomalies. On the MSME side, users can register accounts, link devices, profile appliances, monitor energy use, receive maintenance insights, generate reports, and access system support. For super administrators, the platform provides account management, device whitelisting, energy-saving content, and configuration tools. Evaluated by 50 respondents spanning MSME owners and licensed IT, ECE, and EE experts under ISO 25010 standards, Courant achieved an overall mean rating of 4.52, validating its reliability, functionality, and effectiveness in addressing MSME energy management needs.

Introduction

Background of the Study

Evolving technology altered industries and improved operational efficiency across multiple sectors. Smart systems, data analytics, and Internet of Things (IoT) technology had led to the creation of intelligent solutions that automated operations, optimized energy usage, and improved decision-making. Businesses increasingly rely on innovative technologies to monitor and control vital activities, ensuring long-term viability and efficiency. One of the key areas where technology had a significant impact was power management—the use of systems that tracked, regulated, and optimized the consumption of electrical power. The primary objective of power management systems (PMS) was to provide a stable and reliable electricity supply while minimizing costs and maximizing energy efficiency. Micro, Small, and Medium Enterprises (MSMEs), categorized by size, workforce, and assets, were particularly concerned with electricity consumption due to restricted budgets, limited electrical maintenance capabilities, and the impact on operational expenses.

Micro, Small, and Medium-sized Enterprises (MSMEs) face significant initial hurdles in adopting advanced power management systems, beginning with foundational challenges in utilizing the Internet of Things (IoT). A primary issue is how MSME owners can securely register and create an account for their business and subsequently link their IoT devices to a web application, a process that remains a barrier for many. Even with connected devices, the data's value is limited without proper context; therefore, a critical problem is the lack of a structured process that would allow users to generate profiles for their linked appliances, which is necessary for tracing specific energy consumption sources and ensuring meaningful analysis.

Once data collection is established, the next set of challenges revolves around transforming that data into actionable intelligence. Without detailed appliance profiles, MSMEs cannot effectively monitor and display real-time power consumption and power factor information, leaving them with inconclusive, high-level data. This deficiency extends to a lack of advanced capabilities, as current systems struggle to generate actionable insights from the acquired data to predict probable electrical faults, forcing businesses into a reactive, rather than proactive, maintenance model. Compounding this, there is often no mechanism to notify users in real time if possible issues are detected, preventing timely intervention. Furthermore, businesses struggle to translate raw data into strategy, highlighting the need for a system that can provide comprehensive reports using monitoring data and device behavior, and they lack the means for direct intervention, raising the question of how users can remotely manage their appliances' power status and settings using the application.

Finally, ensuring the system's long-term usability and security presents a third layer of problems. To support adoption and sustained use, there is a clear need for a system that can provide a Help and Learn feature to help users understand system functionalities and power-efficiency best practices, addressing the technical knowledge gap common in the MSME sector. From an administrative perspective, maintaining the system's integrity and security is paramount, creating a need to solve how admins can ensure security through whitelisting of devices and configure the application to protect sensitive business information and guarantee operational reliability for all users.

The developed system aims to serve Micro, Small, and Medium Enterprises (MSMEs) by improving the management of their power consumption and ensuring accurate monitoring of energy usage. MSMEs may benefit from the implementation of the system since it provides real-time monitoring, predictive maintenance alerts, appliance profiling, and remote device control, helping them reduce costs and prevent equipment damage. The system also promotes sustainability by encouraging efficient energy usage and ensuring operational reliability. Furthermore, this study can be a framework that other organizations might use to improve their energy management procedures. It might also be a guide for researchers in the future who want to carry out similar research or create related initiatives.

Objectives of the Study

Specifically, the study aims to:

• Design a management system that is capable of:

  a. Allowing MSMEs to register and create an account for their business through the registration module;

  b. Enabling MSMEs to link the IoT device to the web application through the device identification module;

  c. Letting MSMEs to generate profiles for their appliances through the appliance profiling module;

  d. Providing MSMEs remote management of their appliances' power status through the sockets module;

  e. Allowing MSMEs to monitor power consumption and power factor in real-time via line graph presentation through the monitoring module;

  f. Providing MSMEs with predictive maintenance which encompasses information on potential causes and recommendation for a probable electrical fault through the AI-powered Insights module;

  g. Alerting MSMEs in real-time if possible electrical issues are detected through the notification module;

  h. Enabling MSMEs to generate reports about energy consumption, cost analysis and equipment usage through the report generation module;

  i. Allowing the MSMEs to send inquiries about the system functionalities and issues through the Help module;

  j. Allowing the super admin to post best practices and tips for power-efficiency and app usage through the Learnings module;

  k. Letting super admin to manage MSMEs' accounts via the user management module;

  l. Allowing super admin to whitelist the unique identifier (UID) of the IoT device through the whitelisting module; and

  m. Enabling the super admin to configure the progressive web application through the app and site configuration module.

• Create the system using software tools such as PHP, Python, Visual Studio Code, PlatformIO, MySQL, Laravel Herd, Windows OS, Web Browser, Flask, Laravel, FilamentPHP, TensorFlow, NumPy, SciKit Learn, MQTT Connection Protocol and integrated with hardware components like computer, smartphone, modem, breadboards, PZEM 004T 100A with CT, receptacles, NodeMCU (ESP8266), relay, and fuse.

• Test and improve the developed system in terms of functionality, accuracy and reliability; and

• Evaluate the performance of the developed system based on functional suitability, performance efficiency, compatibility, capability, reliability, security, maintainability, and portability.

Scope and Limitations of the Study

The developed study presents a smart power management system with IoT integration and predictive maintenance, designed for MSMEs to improve energy efficiency through real-time monitoring, early anomaly detection, and data-driven decision-making. Its hardware component, the EDMER (Energy-Driven Monitoring and Evaluation Relay), tracks power consumption and power factor of connected devices, transmitting data to a progressive web application for visualization, predictive analytics, notifications, and reporting. The system is limited to specific modules, with their functions and constraints defined in this section.

The system begins with a Registration and Login Module, where MSME users can create an account or access existing ones, with verification for new accounts. Once registered, they proceed to the Device Identification Module to link their EDMER device by entering its UID and password, ensuring proper activation and security.

Through the Appliance Profiling Module, MSMEs can provide details of their appliances, including expected power and threshold settings for anomaly notifications. The Sockets Module then allows users to view connected appliances and remotely toggle socket power as needed.

The Monitoring Module displays real-time power consumption and power factor data, with graphs that update continuously and provide historical filtering by hour, day, week, or month. Complementing this, the Reports and Insights Module integrates AI-powered predictive maintenance to detect power wastage, anomalies, or potential equipment issues, and enables users to generate customizable reports in CSV or PDF format.

The Notification Module alerts MSMEs of detected irregularities in power readings or socket activity, helping them respond quickly to possible faults. To support users, the Learning and Support Page includes a Help module for inquiries to admins and a Learn module containing articles and guides.

For administrators, the Admin Page provides User Management, Whitelisting, and App and Site Configuration modules. These allow admins to oversee registered MSMEs, whitelist IoT devices for security, configure system settings, and manage content for support modules.

The system’s functions are limited to the detection of consumption and power factor, and remote power toggling for each socket, MSME notification of abnormal consumption levels, analytics, and report generation. This study did not cover features such as directly protecting devices from power surges or voltage fluctuations, operating without a Wi-Fi connection, actively managing—where the system automatically adjusts—the power consumption of connected devices, or autonomously responding to energy usage—aside from triggering a fuse to cut off power during a surge. MSMEs are still responsible for addressing power-related issues or taking action after being notified by the web application.

The developed system includes a combination of hardware and software components. Visual Studio Code served as the primary code editor, with Laravel Herd for local development. Laravel is the major PHP framework, with FilamentPHP used throughout the system. MySQL Workbench handles database management, while TailwindCSS provides UI styling. For interactive features, Livewire and AlpineJS were used. PlatformIO was utilized to program the microcontrollers. The entire system was developed as a Progressive Web Application (PWA), a web application that is installable and cross-platform accessible through a typical internet browser or installed via the browser across multiple platforms.

The hardware side of the system consists of essential devices and modules for execution. A development computer was used for coding and configuration, supported by a Wi-Fi internet connection for network communication. Breadboards were used for circuit prototyping, while a PZEM-004T 100A with CT sensor monitors electrical parameters. Receptacles securely connected electrical devices, while a NodeMCU (ESP8266) with an expansion board acted as the primary microcontroller for sensor data collection and Wi-Fi connectivity. A multi-channel relay module controls device switching, with an overcurrent fuse providing protection. For mobile app deployment and testing, a smartphone device, modem, and computer system were also required.

The developed system was evaluated using ISO 25010:2011 main quality characteristics such as effectiveness, efficiency, satisfaction, Freedom from risk, context coverage of the system. The system was tested by forty (40) MSME owners, five (5) Engineering experts, and five (5) IT experts.

Methodology

The proponents adopted the Rapid Application Development (RAD) methodology for developing the IoT-based system. This model was selected because it promotes rapid prototyping, iterative testing, and continuous user feedback, which are crucial for systems involving both software and hardware components. RAD’s flexibility allows developers to make quick adjustments during the development process, ensuring smooth integration between the IoT device and the web application while minimizing errors and delays.

Figure 1**. Rapid Application Development**

1. Requirements Planning

Kolosky (2024) states that the requirements planning phase lays the groundwork for the project by involving developers, stakeholders, and users in establishing the scope, objectives, and essential requirements. It focuses on rapidly obtaining precise information in order to develop a clear, collaborative project plan that meets corporate requirements and user expectations. The proponents conducted interviews with MSMEs, brainstormed, and collected detailed information regarding the planned study. Additionally, the proponents made plans for the project's full development. By the end of this phase, the proponents had completed the flow of the system, which was already established, and documentation had begun.

2. User Design

Kolosky (2024) describes the user design phase as developing detailed system models and prototypes based on the needs identified during the planning phase. This method enables the early discovery and resolution of difficulties, ensuring that the design remains user-focused and in line with business objectives. The phase ends with a validated and well-defined blueprint for the next development stage. The proponents used the requirements provided to construct wireframes during the design phase, which served as a guide for the rest of the project. They also began the construction of EDMER that collected and transmitted power consumption data. Unit testing ensures that each module performs well in isolation. Integration testing verifies that components communicate properly. Additionally, the proponents created the entity-relationship diagram, data flow diagram, and user interface design for the developed study. The proponents started and plan to continue organizing the documentation during this phase.

3. Rapid Construction

As stated by Kolosky (2024), rapid construction focuses on developing the application's basic functionality using the previously established prototypes and design models. System components are developed and integrated using iterative and incremental processes, with frequent testing and user feedback allowing for continuous modification. This step ensures that improvements are made in real time, resulting in a fully functional application when completed. The proponents focus on the rapid construction of system modules in order to efficiently develop the system's key components. User feedback is constantly received and used to modify system features, improve usability, and guarantee that the final product meets the intended criteria and user expectations.

4. Cutover Phase

When the completed system is placed into production. Final changes, comprehensive testing, and this phase culminates with the system being fully operational and the start of maintenance and support activities to ensure sustained performance and user satisfaction (Kolosky, 2024). The proponents made final changes to resolve any outstanding issues or changes discovered during testing or user evaluations. Once the system is implemented, maintenance operations are carried out to monitor performance, handle unexpected difficulties, and apply appropriate updates, ensuring that the system remains accurate and reliable in real-world applications.

Figure 2. Context Diagram

As in Figure 2, there are three entities interacting with the system: the Admin, the MSMEs, and the EDMER device/s.

Succeeding the entering of login credentials of admins, they register the IoT devices using MAC addresses of the device, which the system is designed to hold as the devices’ UID. From the system, admins receive a login response, a device registration confirmation, and MSME inquiries. MSME inquiries are from business owners that submit questions regarding using the system. After reception of an inquiry, the admin can update the state of the request by either answering the inquiry or rejecting it, a system of moderation necessary for managing questions MSME begins by creating their accounts via registration and providing necessary information for creating an account. After this creation, they are free to log in through login credentials sent to the system.

For logins and registrations, the MSME sends a response. To reiterate, IoT devices come with a pre-registered UID which the MSME needs to enter into the system for Device Identification. This prompts a confirmation of device identification from the system. Furthermore, MSME enters the profiles of linked appliances, including a user-defined name, the type of device, and appliance power rating. Through the entered profiling data, the system returns data insights related to the power rating, as the rest of the data only stems from the incoming power consumption once plugged in. Lastly, the IoT device receives the device configuration from the system. In return, once in use, the device sends power readings and anomaly alerts to the system.

RESULTS AND DISCUSSIONS

Project Description
Courant, a web-based application that aims to help Micro, Small, and Medium-sized Enterprises (MSMEs) addresses challenges in energy consumption and equipment maintenance. Using Internet of Things (IoT) technology such as the NodeMCU microcontroller, PZEM-004T sensors, and relays, the system collects real-time data on voltage, current, and power usage, and stores in a centralized database, presented through a Laravel-based web application enhanced with predictive maintenance features powered by Python machine learning algorithms. With Courant, MSMEs are able to monitor their energy consumption, gain insights through predictive analytics, and automate processes that can potentially lower operational costs and reduce the risk of equipment failure. The target users of the system are MSME owners and administrators seeking efficient and reliable solutions for energy management.

The Courant system is designed to enhance power management for both MSMEs and administrators by integrating a wide range of features. For MSMEs, it offers secure business account registration, device identification for linking IoT devices, and appliance profiling with socket control for remote management. It also provides real-time monitoring of power consumption and power factors through dynamic graphs, while its AI-powered insights and notification modules support predictive maintenance by detecting potential electrical issues and sending alerts. To aid decision-making, the system generates detailed reports on energy usage, costs, and equipment performance, complemented by a help module for inquiries and a learnings module for sharing best practices. On the administrative side, Courant includes user management for account handling, a whitelisting module for secure device registration, and application configuration tools for overseeing both application and site settings, ensuring efficient and reliable system operations.

The prototype is primarily designed to monitor power consumption and power factors, with its functionality restricted to detection, visualization, predictive analytics, report generation, and remote toggling of socket power. It does not extend to advanced functions such as direct protection of appliances from power surges or voltage fluctuations, operating in the absence of a Wi-Fi connection, or autonomously managing energy consumption of connected devices. The system only provides alerts and recommendations; thus, the responsibility for addressing detected electrical issues and implementing corrective measures remains with the MSMEs. Furthermore, the hardware setup relies on specific components—such as the NodeMCU microcontroller, PZEM-004T sensors, relay modules, and a stable internet connection—making the system dependent on both reliable connectivity and proper device configuration. While Courant enhances monitoring and predictive maintenance, it does not fully automate power management processes, thereby limiting its scope to decision support rather than autonomous intervention.

Summary of Findings

Based on the analysis of data, the findings are as follows:

1. Evaluation result of Courant: Revolutionizing Power Management for MSMEs with IoT Integration and Predictive Maintenance Using LSTM Algorithm.

   1.1. Functional Suitability obtained an average mean of 4.6 with a descriptive interpretation of Excellent. This demonstrates that the system’s design adequately covers the specified tasks and goals, allowing users to accomplish them with ease and accuracy.

   1.2. Performance Efficiency received an average mean of 4.49 interpreted as Very Good. This shows that the system is dependable in terms of response times, resource use, and handling capacity, though further improvements may optimize efficiency.

   1.3. Compatibility garnered an average mean of 4.48, which is Very Good. This indicates that the system can effectively perform its intended functions and coexist with other applications while maintaining interoperability.

   1.4. Usability attained an average mean of 4.49, interpreted as Very Good. The system proved user-friendly and simple to operate, ensuring a smooth interaction experience for users.

   1.5. Reliability had an average mean of 4.48, considered Very Good. This shows that the system is reliable, with its modules functioning effectively and consistently according to their intended purpose.

   1.6. Security achieved an average mean of 4.55, interpreted as Excellent. The system ensures data confidentiality, integrity, and authenticity, while safeguarding user privacy and access.

   1.7. Maintainability obtained an average mean of 4.52, which is Excellent. This indicates that the system is well-structured, easy to maintain, and adaptable to modifications or testing when required.

   1.8. Portability received an average mean of 4.51, interpreted as Excellent. This signifies that the system is adaptable, installable, and replaceable across various platforms without significant difficulty.

2. On the implementation of Courant: Revolutionizing Power Management for MSMEs with IoT Integration and Predictive Maintenance Using LSTM Algorithm.

   2.1. A total of 98% of the respondents were in favor of implementing the system because it is reliable, user-friendly, and effective. Courant combines essential modules such as monitoring, predictive maintenance, reporting, and learning resources into one application, making it convenient and beneficial for MSMEs in managing their power consumption.

Conclusions

The following conclusions are gathered based on the evaluation:

1. Courant: Revolutionizing Power Management for MSMES with IoT Integration and Predictive Maintenance Using LSTM Algorithm is a progressive web application that helps Micro, Small, and Medium Enterprises (MSMEs) efficiently monitor and manage power consumption using IoT and AI-powered predictive maintenance. MSMEs can register their businesses, link IoT devices, and create appliance profiles for monitoring. They can remotely control appliance power status and view real-time power consumption and power factor data through interactive graphs. The system’s AI insights detect potential electrical faults, provide recommendations, and send alerts through notifications. Users can also generate reports on power usage and costs, access help for system inquiries, and view energy-saving tips posted by super admins. Additionally, super admins can manage user accounts, whitelist IoT devices, and configure application settings.
   2. The system’s software was created using PHP, Python, Visual Studio Code, PlatformIO, MySQL, Laravel Herd, Windows OS, Web Browser, Flask, Laravel, FilamentPHP, TensorFlow, NumPy, SciKit Learn, MQTT Connection Protocol. On the other hand, its hardware was built with computers, smartphone, modem, breadboards, PZEM 004T 100A with CT, receptacles, NodeMCU (ESP8266), relay, and fuse.
   3. Courant: Revolutionizing Power Management for MSMES with IoT Integration and Predictive Maintenance Using LSTM Algorithm was successfully tested and improved via test scripts and evaluation criteria, wherein the system fulfilled terms of functionality, accuracy, and reliability, passing all tests.
   4. The performance of Courant: Revolutionizing Power Management for MSMES with IoT Integration and Predictive Maintenance Using LSTM Algorithm was successfully evaluated using the ISO 25010, passing the criteria functional suitability, performance efficiency, compatibility, capability, reliability, security, maintainability, and portability, with an average mean of 4.52 with a descriptive interpretation of Excellent.

Recommendations

Based on the foregoing conclusions, the following are recommended for the further improvement of the project:

1. To enhance the predictive maintenance feature to include corrective actions, allowing the system to automatically address or prevent faults when possible.

2. To expand predictive maintenance capabilities to cover issues requiring physical inspection or environmental sensing, such as overheating, frayed wiring, or mechanical damage.

3. To implement measures to minimize delays in real-time reporting caused by internet interruptions.

4. To upgrade the hardware to support appliances with load above 10A (2,200 W).

5. To increase the number of appliances that can be simultaneously connected and monitored to accommodate larger setups and user needs.

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

[image2]: 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