# Design, Implementation and Power Analysis of
## 1 Introduction  
Smart automation is used primarily for patient monitoring [1], activity recognition [2, 3] and energy management [4, 5]. Though smart automation is now made possible with the enormous growth in Internet of Things (IoT); it faces three main difficulties, namely device heterogeneity, inconsistency and conflicting decisions [6]. Heterogeneity is mainly due to the varied volume and format of data from different sensors deployed for sensing the environment. These diverse data become incomparable and unpredictable, leading to contradictions when predicting the environment conditions to proceed further in a sequence of automated actions. Thus, heterogenous data causes inconsistency which eventually ends up in conflicting decisions. The electronic accessories deployed can be categorized into four types, such as basic utilities, comfort gadgets, pleasure-providing appliances and heavyequipment. Basic utilities include various forms of lights and fans that are significant tools leading to undesirable waste of power. Comfort gadgets comprise the newly designed apparatus used for relaxed living such as heating (heaters, induction stoves, kettles), cooling (refrigerators), lifts/escalators, computers, printers, air conditioning and washing (clothes and vessels). Pleasure-providing appliances, mainly utilized for recreation, include televisions, radios and phones. Heavy equipment comprises the massive machineries used in industrial units. Light bulbs prevailing in the small rooms of many storied buildings and in outdoor environments like streets, playgrounds, parks or gardens. The projected model predominantly controls only the lights, categorized under the basic devices as these are found in households of any kind, industries, hospitals and institutions, irrespective of their location across the globe. The control of essential and all-time use equipment leads to a substantial power savings. In developing countries like India, the use of incandescent bulbs is still prevalent [7], so the authors have come up with a device that could control both incandescent and LED light bulbs to help developing countries minimize the power consumption. Further, from the cited analysis [7] it is found that 60 W and 100 W are the most popular incandescent bulbs used, so in experiments the authors use a 60 W incandescent light bulb which has 800 Lumens. Similarly, the authors chose a 8 W LED bulb which has 800 Lumens. For testing the performance of the proposed device with low power consuming appliances, a light bulb of 0.5 W is also used. Based on the previous work in lighting control by different authors around the world, light bulb control was found to be achieved by nine methods: timer control, daylight-linked control, occupancy detection, individual tuning, centralized tuning, image-based, video analytics, neural network-based control and hybrid control (Figure 1). Timer-based light control system were designed to set the status of light bulbs based on a preprogrammed time [8]. Daylight-linked control systems [9; 10; 11] were devised to operate by evaluating the daylight illuminance. The system design involves daylight availability, intensity evaluation and the assessment of daylight values. Based on the illuminance of daylight, dimming of light bulbs is performed. The two aspects required in daylight-linked systems are photosensors and dimming of light bulbs. Dimming affects the power quality of light bulbs [12]. In daylight intensity estimation, photosensors play a major role. The problems faced by photosensors are the distribution of daylight and artificial lighting in the space in which they are placed; the absence of explicit guidelines for the setting, positioning and commissioning of the photosensor; the spectral composition of lighting; the ambient light intensity and the field of view [13]. A decision-making technique [14] capable of identifying the best photosensor placement with variable field of view was analyzed based on three criteria.