Indonesian J our nal of Electrical Engineering and Computer Science V ol. 43, No. 1, July 2026, pp. 179 ∼ 191 ISSN: 2502-4752, DOI: 10.11591/ijeecs.v43.i1.pp179-191 ❒ 179 REHA: r eal-time IoT -based ener gy efcient home automation system using ESP8266 and PIR motion sensors Md. Kamal Ibne Suan 1 , P oly Bhoumik 2 , Selina Sharmin 3 , Nazma T ara 1 1 Department of Computer Science, National Uni v ersity , Gazipur , Bangladesh 2 Department of Computer Science and Engineering, Daf fodil Institute of Information and T echnology , Dhaka, Bangladesh 3 Department of Computer Science and Engineering, Jag annath Uni v ersity , Dhaka, Bangladesh Article Inf o Article history: Recei v ed Jan 15, 2026 Re vised Jun 2, 2026 Accepted Jun 27, 2026 K eyw ords: Ener gy management system ESP8266 IoT -based home automatio PIR motion sensor Smart home ABSTRA CT T echnological de v elopments ha v e impro v ed l i ving standards, leading to greater demand for home automation based on the internet of things (IoT) concept. This study addresses the limitations of e xisting home automation systems, which are often costly , comple x, and lack ener gy-sa ving features. A lo w-cost IoT -based home automation system is de v eloped using the ESP8266 NodeMCU and PIR motion sensors to enable both remote control and automatic operation of house- hold appliances. It uses the Blynk platform for cloud-based monitoring with smart motion-bas ed logic to minimize unnecessary po wer consumption. The e v aluation is conducted through v arious controlled scenarios and an estimate- based ener gy analysis deri v ed from standard appliance ratings. Experimental results sho wed a reduction in household ener gy consumption of about 13–15%. The proposed system of fers a cost-ef fecti v e, practical approach to smart home ener gy management by combining af fordability , automation, and measurable ef- cienc y impro v ements. This is an open access article under the CC BY -SA license . Corresponding A uthor: Nazma T ara Department of Computer Science, National Uni v ersity Gazipur , Bangladesh Email: nazma.tara@nu.ac.bd 1. INTR ODUCTION The internet of things (IoT) has emer ged as a transformati v e technology in home automation, enabling real-time communication among de vices, sensors, and users [1]. One of the most impactful applications of IoT is in smart ener gy management, where it enabl es the ef cient use of electrical resources in residential en viron- ments [2]. Gi v en the gro wing ener gy demand and en vironmental concerns, de v eloping an IoT -based, ener gy- ef cient system for smart homes is both pertinent and crucial. An IoT -based smart home can monitor , analyze, and control ener gy-intensi v e appliances lik e lights, f ans, refrigerators, and HV A C systems. Automation and remote control allo w users to minimize w asteful ener gy use and mak e informed ener gy-related decisions. Additionally , combining sensor -based automation with web-based or smartphone interf aces impro v es ef cienc y and user comfort. According to recent research, IoT systems signicantly reduce household ener gy consumption by using s ensors and structured architectures to dynamically modify appliances based on real- time data [2], [3]. Th e main aim of this w ork is to de v elop an IoT -based ener gy management system for a smart home, with a lo w-cost, simple, and ef cient house system as the k e y concentration on the Node MCU ESP8266 microcontroller to de v elop a home automation system. Gang a et al. [4] of fers a lo w-cost, IoT -based smart home ener gy management system intended to increase accessibility and ener gy ef cienc y . J ournal homepage: http://ijeecs.iaescor e .com Evaluation Warning : The document was created with Spire.PDF for Python.
180 ❒ ISSN: 2502-4752 The system uses a NodeMCU microcontroller with b uilt-in W i-Fi, based on the ESP8266 system-on- chip (SoC) from espressif systems, to control household de vices. All sensors are connected to the NodeMCU, which collects and transmits real-time data to the Blynk and Sinric Pro cloud serv ers, enabling IoT inte gration with Amazon Ale xa for v oice-based control. The NodeMCU is programmed to communicate with the Blynk serv ers via both local and global netw orks, ensuring reliable, continuous system connecti vity . The o v erall architecture of the IoT -based ef cient ener gy consumption system is presented in Fi gure 1. The system ensures intelligent appliance operation without user interv ention by inte grating ener gy optimization techniques and motion-based automat ion. P articular focus is placed on inclusi vity , ensuring that the s ystem is both scalable and user -friendly for the general public and simple to use for people with ph ysical disabilities and the elderly . Additionally , the platform ’ s cloud inte gration enables safe data access, remote control, and future gro wth. This w ork helps close the digital di vide and adv ances global objecti v es for smart ener gy conserv ation and sustainable li ving by fusing af fordability , automation, and sustainability . Figure 1. Ov erall architecture of the proposed IoT -based smart home ener gy management system Although these scalable solutions address technical challenges to lo wer electricity costs, promote sustainability , and enable broader smart grid inte gration, e xisting IoT -based home automation systems still f ace se v eral important limitations, such as the inability to operate ef fecti v ely o v er long distances and the absence of scalable, cost-ef fecti v e, and practical solutions suitable for l ar ge-scale adoption. This research aims to bridge these g aps by proposing a lo w-cost, sensor -dri v en automation system with e xplicit ener gy-sa ving analysis. This paper is or g anized as follo ws: in section 1, introduce the prototype by discussing its goals, the problems with earlier approaches, and the adv antages of our method. In section 2, we present background and a literature re vie w , the goals of their studies, the algorithms used, and the distincti v e features of their research. The proposed prototype discusses the systematic design, implementation, and e v al uation of the IoT - based ener gy management system in section 3. It ensures that the researc h is v alid from a scientic perspecti v e, repeatable, and measurable. In section 4, presents an analysis of the proposed prototype’ s outcomes. Finally , we conclude the paper in section 5. 2. LITERA TURE REVIEW This section re vie ws e xisting research on IoT -based home automation and ener gy management sys- tems. It critically analyzes prior approaches in terms of system architecture, communication technologies, cost, and ener gy optimization capabilities. Based on thi s analysis, the k e y limitations of e xisting systems are identied, leading to the formulation of the research g ap and the contrib utions of this w ork. 2.1. Existing systems and comparati v e analysis This subsection presents the benets and dra wbacks of v arious system architectures and co v ers a range of netw ork technologies used to control household appliances, including bluetooth, W i-Fi, and ZigBee. This section re vie ws and contrasts the main smart home studies on cost, communication strate gies, scalability , and usability . It sho ws that man y of the systems lack ed true automation logic, had only mobile control, or were unsuitable for lo w-income households. Highlights signicant research g aps, including poor remote access, high setup costs, limited multi-control support, and limited real-time automation. These shortcomings under - score the need for a more user -friendly , scalable, and accessible IoT -based home automation system. Indonesian J Elec Eng & Comp Sci, V ol. 43, No. 1, July 2026: 179–191 Evaluation Warning : The document was created with Spire.PDF for Python.
Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752 ❒ 181 Gill et al. [5], the author uses ZigBee as a communication protocol to design an adaptable and ef ci ent home automation architecture. Another study introduced a W i-Fi-based IoT frame w ork for Internet-based home appliance monitoring and control. This approach used smartphones as control interf aces and a Raspberry Pi as the central serv er to ensure real-time communication and user accessibility [6], [7]. Researchers ha v e addressed gro wing concerns about the security of IoT home systems by proposing onion-based multipath and split-channel g ate w ays that circumv ent T or’ s scalability and bandwidth limitations [8]. These systems aim to increase security without compromising performance, especially for older users [9]. The w ork sho wed ho w 5G-enabled IoT can support blockchain-based smart applications across sectors such as homes, healthcare, agriculture, and transportation, while highlighting unresolv ed technical issues [10]. T able 1 presents a comparati v e analysis of some e xisting IoT -based home automation approaches and their components. T able 1. Comparati v e analysis: e xisting IoT -based home automation approaches and their hardw are components SL Author Main focus Components 1 Atzori et al. [1] Uses Arduino and Bluet ooth for gesture-based and smart- phone control via Android de vice. ⋆ Arduino Me g a 2560 ⋆ 16x2 LCD dis- play ⋆ Google Assistant App 2 Kim et al. [2] Smart meters for ener gy monitoring, control, and billing on the demand side. ⋆ TM4C129x MCU ⋆ MSP430 ⋆ ES P32 module 3 Shaikh et al. [3] Inte grates non-smart appliances using the homer gy box. ⋆ Arduino Me g a 2560 ⋆ ESP8266 ⋆ 4- channel relay board 4 Sureshkumar [4] Smart meter with web/mobile control of ener gy loads. ⋆ Arduino ⋆ Raspberry Pi ⋆ I2C LCD adapter 5 Gill et al. [5] Real-time ener gy display via smart meter and GPRS. ⋆ ARM Corte x M4 MCU ⋆ GSM/GPRS module ⋆ Relay dri v er 6 P a vithra and Balakrishnan [6] Ef cient scheduling algorithm with pri v ac y . ⋆ 4-channel relay ⋆ ADMM algorithm 7 K or et al. [7] Bluetooth-enabled Arduino system with sensors for automa- tion. ⋆ PIR sensor ⋆ Relay board ⋆ R TC mod- ule (DS1307) 8 Y ang et al. [8] Lo w-cost general home automation via Bluetooth. ⋆ Arduino Uno ⋆ HC-06 Bluetooth ⋆ Ul- trasonic sensor 9 K or et al. [9] Real-time EMS using mesh and BI tools. ⋆ T emp/Humidity sensor ⋆ Microcon- troller ⋆ Serv ers 10 Mist ry et al. [10] RECoS smart sock et system to minimize ener gy use. ⋆ ELC module ⋆ PTC module ⋆ Zigbee On the other hand, mobile sink path-planning techniques in IoT -based wireless sensor netw orks (WSNs) were thoroughly e xamined, and their usefulness in elds such as home automation, smart cities, healthcare, and weather monitoring w as demonstrated [11]. Kaur et al. [12], it is also suggested that lo wer latenc y and increased netw ork longe vity can be achie v ed with a deep reinforcement learning-based routing al- gorithm. Edge computing and IoT concepts were used to create an inte grated, af fordable smart home platform. The system’ s goal is to combine v arious home autom ation features, such as ener gy ef cienc y , appliance con- trol, and security , into a single, user -friendly architecture [13]. V ulnerabilities in de vice communication and cloud-based service inte gration were identied in a thorough security analysis of home automat ion systems, necessitating impro v ed system design protections [14], [15]. Se v eral studies de v eloped lo w-cost IoT -based home automation prototypes using microcontrollers and mobile apps, emplo ying Bluetooth for indoor control and Ethernet for outdoor connecti vity [16]-[18]. Multi-protocol wireless g ate w ays using ESP ha v e no w been de v eloped and tested, enabling m ulti-hop communication a n d demonstrating reliable e xtended co v erage for s mart home automation [19]. The inte gra- tion of IoT cloud services of fers signicant benets for smart homes b ut requires rob ust security measures to mitig ate vul nerabilities [20], [21]. Lo w-cost microcontroller -based prototypes using Bluetooth a n d Ethernet ha v e b e en de v eloped to enable af fordable local and remote smart home control [22]. Smart home systems in- creasingly emphasize personalized mobi le-based interf aces that allo w users to rem otely control home functions according to indi vidual preferences [23]. Comprehensi v e smart home systems that inte grate automation, safety , security , and ener gy ef cienc y while operating with minimal computational and netw ork resources. Lo w-cost Arduino and Bluetooth-based solutions ha v e demonstrated that real-time home control through Android appli- cations is both practical and ef fecti v e [24]. REHA: r eal-time IoT -based ener gy ef cient home automation system ... (Md. Kamal Ibne Suan) Evaluation Warning : The document was created with Spire.PDF for Python.
182 ❒ ISSN: 2502-4752 2.2. Resear ch gap and pr oblem statement Existing IoT -based home automation sys tems still f ace se v eral important limitations. One major chal- lenge is the inability to operate ef fecti v ely o v er long distances, as man y studies ha v e not adequately addressed reliable remote connecti vity for smart home control. In addition, current systems often lack reliable motion- detection mechanisms, which leads to missed automation triggers and reduced responsi v eness in smart-home en vironments. Another signicant limitation is the a b s ence of scalable, cost-ef fecti v e, and practical solutions suitable for lar ge-scale adoption. These g aps highlight the need for impro v ed IoT architectures that support long-distance communication, dependable motion-based automation, and scalable designs that are easy to im- plement in real-w orld smart home applications. 2.3. Contrib utions of this w ork T o address the identied limitations, this study proposes a comprehensi v e, practical IoT -based smart home solution that enhances connecti vity , reliability , and scalability . Hence, this paper highlights three k e y aspects. First, it proposes a h ybrid control architecture that inte grates manual switching, PIR-based occu- panc y detection, and cloud-based remote control within a unied lo w-cost frame w ork. Second, it introduces a conte xt-a w are ener gy estimation model tailored to residential usage patterns in de v eloping countries, incorpo- rating locally rele v ant appliance data and beha vioral assumptions. Finally , the system demonstrates a practical balance between af fordability , automation, and ener gy ef cienc y , making it suitable for lar ge-scale adoption in resource-constrained en vironments. This analysis helped t o identify optimization points in system design and impro v e ener gy management logic. 3. METHODOLOGY AND SYSTEM DESIGN This section presents the o v erall methodology and system design of the proposed IoT -based home au- tomation system. It describes the system architecture, hardw are and softw are components, and data collection procedures. In addition, the operational logic of the system is e xplained to ensure clarity , reproducibility , and systematic e v aluation. 3.1. System o v er view and ar chitectur e The functional block diagram in Figure 2 illustrates the o v erall operation of our proposed IoT -based ener gy management system, which inte grates automatic and manual control of home appliances via a central- ized microcontroller and wireless communication. 3.2. Hard war e and softwar e components T o complete our system de v elopment, we require some softw are and hardw are components. The hardw are components that we used to de v elop our home automation system are listed in Figure 3. The softw are tools include the Arduino IDE for coding and uploading programs, web bro wsers such as Google Chrome or Mozilla Firefox for accessing web interf aces, and Blynk serv ers for enabling real-time communication and remote control through the Blynk mobile application. Figure 2. Functional block diagram of the proposed IoT -based home automation system Figure 3. Hardw are components of the proposed IoT -based home automation prototype Indonesian J Elec Eng & Comp Sci, V ol. 43, No. 1, July 2026: 179–191 Evaluation Warning : The document was created with Spire.PDF for Python.
Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752 ❒ 183 3.3. Data collection and e v aluation methodology T o v alidate the system’ s performance, data were collected using the follo wing methods: − Surv e ys: conducted with users who interacted with the prototype system to assess usability and user satis- f action. − Experiments: multiple test scenarios were created in controlled en vironments to measure system beha vior , delay , and accurac y . − Direct measurements: po wer usage, de vice runtime, and PIR detection acti vity were meas ured using multi- meters, timers, and data logs from the Blynk app. T o e v aluate the performance of the proposed Prototype, a quantitati v e e xperimental methodology is emplo yed in a controlled residential en vironment, as described in the s tudy . The system is tested using four household appliances connected through a NodeMCU (ESP8266), PIR sensors, relay modules, and manual switches. Motion detection is performed using PIR sensors with a detection range of approximately 5–7 meters and a 120° eld of vie w . Each relay channel supports a maximum load of 220V/10A, enabling safe control of typical household appliances. This ensures t h a t appliances operate only when user intent and occupanc y are both satised. PIR sensors were selected for their lo w cost, lo w po wer consumption, and suitability for indoor occupanc y detection, compared with alternati v es such as ultrasonic or camera-based systems. Ho we v er , ener gy consumption and cost sa vings are estimated analytically using standard appliance po wer ratings and assumed daily usage hours, rather than real-time ener gy meters. The comparison between these tw o conditions sho wed an approximate ener gy reduction of 13–15%, depending on household size. This methodology ensures a balance between e xperimental v alidation of system beha viour and analytical estimation of ener gy ef cienc y , pro viding a practical and reproducible e v aluation frame w ork. 3.4. System operation This prototype uses Algorithm 1 to create an IoT -based, ener gy-ef cient home automation syst em using the ESP8266 and the Blynk platform. Algorithm 1 IoT -based smart home automation system 1: Initialize W iFi credentials, Blynk, and SinricPro services 2: Congure RELA Y1–RELA Y4 as OUTPUT and B UTT ON1–B UTT ON4 as INPUT PULLUP 3: Set all relays to OFF state 4: Connect to W i-Fi, Blynk cloud, and SinricPro serv er 5: while system is running do 6: Ex ecute Blynk.run() and SinricPro.handle() 7: f or each b utton i = 1 to 4 do 8: if b utton i is pressed then 9: T oggle relay i , update output, and synchronize state with Blynk 10: end if 11: end f or 12: if command recei v ed from SinricPro then 13: Identify de vice ID, update corresponding relay state, and apply change 14: end if 15: if command recei v ed from Blynk app then 16: Read virtual pin v alue, update corresponding relay state, and apply change 17: end if 18: end while 4. IMPLEMENT A TION AND RESUL T AN AL YSIS This section presents the implementation of the proposed system and analyzes its performance under v arious e xperimental conditions. It includes e xperimental setup, system w orko w , control logic, load capacity analysis, performance e v aluation, cost analysis, and ener gy cons umption assessment. In addition, a compara- ti v e analysis with e xisting systems is pro vided to v alidate the ef fecti v eness of the proposed approach. 4.1. Experimental setup De v eloping the proposed IoT -based home automation system requires specic hardw are and softw are components. Figure 4 and Figure 5 sho w the circuit diagram and the ph ysical implementation of our proposed prototype, respecti v ely . The e v aluation is conducted o v er multiple e xperimental c ycles, with 50 trials per load condition and 24-hour usage scenarios repeated according to typical household patterns. REHA: r eal-time IoT -based ener gy ef cient home automation system ... (Md. Kamal Ibne Suan) Evaluation Warning : The document was created with Spire.PDF for Python.
184 ❒ ISSN: 2502-4752 A comparati v e analysis is performed between the baseline conditions (m anual operation without automation) and IoT -based conditions (automated control using motion detection, mobile application, and manual o v erride). Figure 4. Circuit diagram of the proposed prototype in Proteus softw are Figure 5. Ph ysical implementation of the de v eloped IoT -based home automation prototype In the baseline case, appliances operate on x ed schedules, often leading to unnecessary ener gy con- sumption, whereas in the IoT -enabled system, appliances are acti v ated only when occupanc y is detected, im- pro ving ef cienc y . System performance metrics, including response time (approximately 0.5–2.0 seconds), switching accurac y , and PIR sensor acti vity , are measured directly using Blynk logs, Arduino serial monitor - ing, and manual observ ation. 4.2. System implementation and w orko w After connecting all hardw are components and completing the programming setup, we tested the system by running all components according to the proposed system design sho wn in Figure 6. Figure 6. Operational w orko w of the proposed system demonstrating data o w 4.3. Load capacity analysis This prototype w as successfully implemented and tested under real-w orld conditions. During the prototyping phase, se v eral electronic components (transistors, optocouplers, and diodes) were damaged by high-v oltage spik es. T o ensure that all components minimize operating v oltage and current to pre v ent f ailure. T otal load capacity: we used a 1 . 5 m m 2 copper wire, which supports a maximum current of 15 A. W ith a standard line v oltage of 220 V, the total supported load capacity is: T otal Po wer = 220 V × 15 A = 3300 W = 3 . 3 kW (1) Thus, the system can safely handle up to 3 . 3 kW of connected electrical l oad under ideal conditions. Per -channel load capacity: each relay channel used in the system is rated for 220 V , 10 A. Therefore, the maximum po wer capacity per relay-controlled channel is: Channel Po wer = 220 V × 10 A = 2200 W = 2 . 2 kW (2) This implies that each appliance or circuit connected to a single relay channel should not e xceed 2 . 2 kW. Indonesian J Elec Eng & Comp Sci, V ol. 43, No. 1, July 2026: 179–191 Evaluation Warning : The document was created with Spire.PDF for Python.
Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752 ❒ 185 4.4. Contr ol logic and system scenarios Figure 7 presents the e xperimental results of the proposed home automation system under v arious operating scenarios using both the web serv er and the Blynk mobile application. The sequence of images illustrates the complete control w orko w , including interf ace initialization, remote load acti v ation, and motion- based control mechanisms. Specically , Figure 7(a) sho ws the web-based control interf ace aft er establishing the serv er connection, while Figure 7(b) presents the initial state of the Blynk application with all loads turned OFF . The acti v ation of Load 1, Load 2, Load 3, and Load 4 is demonstrated in Figures 7(c), 7(d), 7(e), and 7(f), respecti v ely . Figure 7(g) illustrates the condition in which all loads are acti v ated simultaneously through the mobile application. Finally , Figures 7(h) and 7(i) demonstrate the system beha vior under motion-based operation, where selecti v e deacti v ation occurs when motion is not detected and full acti v ation is achie v ed when motion is detected. These results conrm that the proposed system performs consistently across dif ferent operating scenarios. (a) (b) (c) (d) (e) (f) (g) (h) (i) Figure 7. Experimental results demonstrating real-time control operations through web and mobile interf aces under dif ferent switching scenarios. (a) Phone and control interf ace after web serv er connection, (b) Initial Blynk interf ace (all OFF), (c) Load 1 ON via Blynk and Load 1 remote acti v ation, (d) Control of Load 2 using the Blynk mobile interf ace, (e) Acti v ation of Load 3 using the Blynk mobile application, (f) App-based control and acti v ation of Load 4, (g) Full load acti v ation using the Blynk mobile interf ace, (h) Load status with all switches ON b ut selecti v e deacti v ation based on motion, and (i) Load status with all switches ON and all motion detected The web interf ace and our observ ation of the system’ s response to ON/OFF commands. These are the system’ s real-time control functionality and responsi v eness. The results of each control operation were captured as images and are discussed belo w: T able 2 sho ws the logic for light control based on three inputs: a ph ysical switch, a mobile app s witch, and a PIR motion sensor . V arious operational scenarios were tested after connecting the system to actual appliances. The control operations for each appliance’ s output are gi v en belo w for visual v alidation of images. − Ph ysical switch: manually , when ON (1), the Light turns ON, and the PIR sensor detects that motion. − Mobile app swi tch: in remote control (Smartphone), when ON (1), the Light turns ON based on motion detection. REHA: r eal-time IoT -based ener gy ef cient home automation system ... (Md. Kamal Ibne Suan) Evaluation Warning : The document was created with Spire.PDF for Python.
186 ❒ ISSN: 2502-4752 − PIR sensor: in-room motion is detected when the return v alue is 1. − Output (Light ON/OFF): if motion is detected, the Light is turned ON (1) (PIR = 1 ), and the mobile app switch is ON. The boolean e xpression of this logic is: Light = ( Ph ysical S witch ∨ Mobile App Switch ) ∧ PIR Sensor T able 2. Logic truth table for system inputs (switch, mobile, PIR sensor) and resulting appliance state Ph ysical switch Mobile app switch PIR sensor Light (ON/OFF) 0 0 0 0 (OFF) 0 0 1 0 (OFF) 0 1 0 0 (OFF) 0 1 1 1 (ON) 1 0 0 0 (OFF) 1 0 1 1 (ON) 1 1 0 0 (OFF) 1 1 1 1 (ON) 4.5. P erf ormance e v aluation The system’ s performance w as assessed for both indi vidual loads and for all loads running s imultane- ously under a v ariety of conditions. T o ensure reliability and response accurac y , each scenario w as tested mul- tiple times. T able 3 summarizes the comprehensi v e testing results. As demonstrated, e v ery load w as completed successfully , achie ving a 100% success rate. The a v erage control delay w as approximately 1 second from the command to the load response. F or safety reasons, we ha v e included a 1-second delay in our ESP8266 code. Therefore, it ta k e s about a second to e x ecute a load after sending a command under normal circumstances. There are times, though, when the delay might be less than 0.5 seconds. This occurs when the user sends a command just before the ESP8266 updates the serv er . Ho we v er , because our system uses the internet, the maximum netw ork latenc y we sa w w as about 2 seconds. On the other hand, since our system operates o v er the internet, the maximum delay we observ ed due to netw ork latenc y is around 2 seconds. T able 3. Performance e v aluation of the proposed system in terms of response accurac y , ef cienc y , and control delay No. Loads Number of attempts Successful attempts Ef cienc y A vg. Delay (sec) 1 LED 1 50 50 100% 1 2 LED 2 50 50 100% 1 3 LED 3 50 50 100% 1 4 LED 4 50 50 100% 1 5 All Loads 50 50 100% 1 4.6. Cost analysis The system cost of the IoT -based home automation prototype is sho wn in T able 4. The approximate total cost of our prototype is 1,500 BDT (T aka). This study assesses the usefulness of an IoT -based smart home automation system across dif ferent-sized residential settings. T able 4. Cost breakdo wn of hardw are components used in the proposed IoT -based home automation prototype No. Component Quantity Price (BDT) 1 NodeMCU W i-Fi module 1 420 2 4-Channel 5V relay board 1 290 3 PIR sensor 4 380 4 1N4007 diode 5 20 5 10 k Ω resistor 10 20 6 5V 2A adapter DC po wer supply 1 250 7 Push b utton switch (4-pin) 5 20 8 Male and female jumper wires – 100 T otal estimated cost 1,500 Indonesian J Elec Eng & Comp Sci, V ol. 43, No. 1, July 2026: 179–191 Evaluation Warning : The document was created with Spire.PDF for Python.
Indonesian J Elec Eng & Comp Sci ISSN: 2502-4752 ❒ 187 4.7. Ener gy consumption and sa ving analysis Complementing the performance e v aluation presented in subsection 4.5, this section analyzes dai ly household appliance usage to quant ify ener gy consumption using the appliance po wer ratings and estimated daily usage summarized i n T able 5. The resulting ener gy consumption estimates are then use d to e v aluate the potential cost sa vings presented in T able 6. T able 5. Household appliance po wer ratings and estimated daily usage for ener gy consumption analysis Room/Appliance type De vice details Po wer (W) Daily usage (Hrs) Bedroom Light + F an Light = 25 14 Dining Light + F an F an = 80 14 Dra wing Light + F an TV = 100 8 Li ving Light + F an Electric Iron & Rice Cook er = 1000 10 V eranda Light Refrigerator = 150 6 Kitchen Li ght + Ex. F an Micro w a v e = 1200 6 Bathroom Light + Ex. F an Exhaust F an = 45 4 T able 6. Comparati v e analysis of ener gy consumption, cost sa vings under con v entional and IoT -based automation Cate gory Appliance Daily Monthly Con v . Cost IoT Sa v e/Day IoT Sa v e/Mon IoT Cost Final Cost T ype (Wh) (kWh) (BDT) (Wh) (kWh) Sa v e (BDT) (BDT) Small home Bedroom (2) 2560 76.80 687.36 320 9.6 85.92 601.44 (700 sq. feet) Dining 1280 38.40 343.68 160 4.8 42.96 300.72 Dra wing 1280 38.40 343.68 160 4.8 42.96 300.72 Kitchen 720 21.60 193.32 90 2.7 24.17 169.16 Bath (2) 1440 43.20 386.64 180 5.4 48.34 338.32 T otal — 1954.68 — — 244.34 — 1710.35 Medium home Bedroom (3) 6975 209.25 1872.78 930 27.9 249.72 1623.09 (1000 sq. feet) Dra wing 3900 117.00 1047.15 520 15.6 139.62 907.53 Dining 2550 76.50 684.68 340 10.2 91.29 593.39 Kitchen 560 16.80 150.36 140 4.2 37.59 112.77 Bath (2) 440 13.20 118.14 220 6.6 59.08 59.08 V eranda (2) 240 7.20 64.44 80 2.4 21.48 42.96 Entrance 240 7.20 64.44 80 2.4 21.48 42.96 T otal — 4001.99 — — 620.24 — 3381.76 Lar ge home Bedroom (5) 11625 348.75 3121.30 1550 46.5 416.20 2705.15 (2000 sq. feet) Dra wing 3900 117.00 1047.15 520 15.6 139.62 907.53 Dining 2550 76.50 684.68 340 10.2 91.29 593.39 Li ving 3525 105.75 946.46 470 14.1 126.20 820.27 Kitchen 560 16.80 150.36 140 4.2 37.59 112.77 Bath (3) 660 19.80 177.21 330 9.9 88.62 88.62 V eranda (2) 480 14.40 128.88 160 4.8 42.96 85.92 Entrance 240 7.20 64.44 80 2.4 21.48 42.96 T otal — 6320.49 — — 963.92 — 5356.58 Appliance le v el po wer ratings and usage durations form the basis for estimating baseline ener gy demand and e v aluating the impact of the proposed IoT -based ener gy management system. Daily ener gy consumption for each appliance is calculated using (3). Ener gy (Wh) = Po wer (W) × Usage (Hours/Day) (3) REHA: r eal-time IoT -based ener gy ef cient home automation system ... (Md. Kamal Ibne Suan) Evaluation Warning : The document was created with Spire.PDF for Python.
188 ❒ ISSN: 2502-4752 Which pro vides the baseline ener gy demand under con v entional operation. Building on this baseline, T able 6 assumes that the proposed IoT -based prototype enables approximately 2 hours of a v erage daily en- er gy sa vings per appliance through motion-based automation, intelligent scheduling, and remote control. The assumed reduction of approximately 2 hours/day is based on observ ed idle-time elimination during controlled e xperiments and supported by typical occupanc y-dri v en automation beha vior reported in prior IoT ener gy man- agement studies [25]. The po wer consumption v alues of indi vidual household appliances listed in T able 5 are adopted from publicly a v ailable data published by the Bangladesh Po wer De v elopment Board (BPDB/PDB) [26], ensuring that the electrical ratings reect locally rele v ant standards and gri d conditions. These ratings include commonly used residential appliances such as lights, f ans, tele visions, refrigerators, micro w a v e o v ens, electric irons, rice cook ers, and e xhaust f ans. Using of cial BPDB data enhances the reliability and applicability of the ener gy consumption analysis for Bangladeshi households. The daily usage hours presented in T able 5 are intentionally assumed to be approximately tw o hours higher than t he reference v alues reported in the Lighting Research Cen- tre (LRC), Rensselaer Polytechnic Institute, USA [27]. This adjustment is based on realistic socio-economic and cultural conditions in Bangladesh, where w omen, children, and elderly f amily members typically remain at home for longer periods than in households in the United States. As a result, lighting, f ans, and household appliances are operated for e xtended periods, particularly during daytime hours. The ener gy and cost sa vings sho wn in T able 6 demonstrate that the proposed system can signicantly reduce daily and monthly electricity consumption across small, medium, and lar ge residential settings. These ndings v alidate the ef fecti v eness of the IoT -based automation frame w ork in achie ving measur able ener gy and cost reductions while maintaining user comfort under realistic residential usage conditions in Bangladesh. Figure 8 illustrates a comparati v e analysis of ener gy costs across small, medium, and lar ge homes, with and without IoT -based aut omation o v er 12 months. First, a 700-square-foot small house sho ws an annual ener gy cost reduction of about 4,700 BDT , or 13%. This illustrates ho w small monthly sa vings add up to signicant annual benets. Then, for a medium-si zed home with 1000 square feet, annual electricity costs drop from 48.02 thousand BDT to 40.58 thousand BDT , sa ving 7.44 thousand BDT (15.5%), mostly because of en vironment-responsi v e f an control, automated lighting, and optimized appliance usage. Additionally , IoT automation reduces the unnecessary operation of lighting and air conditioning systems in a lar ger 2000-square- foot home, where ener gy inef cienc y is more noticeable under manual control. This results in annual sa vings of about 11,570 BDT , or a 15.25% reduction in electricity costs. All things considered, these results sho w that IoT -based home automation signicantly increases ener gy ef cienc y and of fers gro wing nancial benets as home size and ener gy demand gro w . Figure 8. Compression of ener gy costs for small, medium, and lar ge home ener gy costs 4.8. Comparati v e analysis with existing systems T able 7 compares the proposed system with se v eral e xisting IoT -based home automation solutions. The comparison co v ers k e y aspects such as hardw are platform, communication method, sensors, cloud in- te gration, ener gy optimization, e v aluation approach, response delay , and o v erall cost. While most pre vi- ous systems ei ther lack proper ener gy-sa ving features or in v olv e higher costs and comple xity , the proposed ESP8266 NodeMCU-based system deli v ers ef fecti v e motion-based ener gy optimization at a v ery lo w cost and wit h good respons e time ( ∼ 1 s). This mak es it a highly practical and af fordable solution, especially for resource-constrained en vironments in de v eloping re gions. Indonesian J Elec Eng & Comp Sci, V ol. 43, No. 1, July 2026: 179–191 Evaluation Warning : The document was created with Spire.PDF for Python.