## Maman Abdurohman* , Aji Gautama Putrada* , Sidik Prabowo* , Catur Wirawan Wijiutomo* and Asma Elmangoush**## |

The exposure value (lx) | LED lighting (%) |

≤100 | 100 |

>100 and ≤150 | ~80 |

>150 and ≤200 | ~72 |

>200 and ≤250 | ~41 |

>250 and ≤300 | ~25 |

>300 and ≤350 | ~9.8 |

>350 | 0 |

The probe is the measuring point of the system to obtain data. The probe is placed between the control box to be measured and the power supply. Fig. 8 shows the spot of probe placement. The number of Probes are three pieces, two pieces for measuring voltage that is arranged in parallel with the phase wires and neutral wires. Meanwhile, the current probe is in clamp shape, mounted on the phase cable.

4.2 Measurement and Data Analysis Based on the measurements results carried out in one minute duration during 24 hours, measurement of power consumption data with both smart lighting systems as well as regular power consumption is obtained. Fig. 9 shows a diagram of power consumption. Power usage data is retrieved by using the Power Harmonics and Analyzer. Data taken in 1 minute intervals over a span of 24 hours, producing 1,441 pieces of data RMS voltage (V_{RMS}) and the RMS current (I_{RMS}) and its real power. RMS is the Root Mean Square value of voltage or alternating current. VRMS and IRMS are used, since voltage and an alternating current do not have a linear value due to the nature of its sinusoidal. The real power (P) of V_{RMS} (V) and I_{RMS} (I) is expressed as

where *t* is time, and *Q* is electric charge.

Obtaining the value of current and voltage in the form of RMS is important, particularly for systems working with alternating current (AC) and the nonlinear loads.

*Pt* is the power (*P*) measured at time duration *t*. Measurements were made at intervals of 1 minute. Meaning that the distance from one measurement of *Pt* to the next *Pt* measurement is 1 minute.

Attaining Energy

Power (*P*) is the amount of work per unit of time, which is expressed as

where *P(t)* is power as a function of time, *E* is energy, and *Δt* is time interval. From (2), energy (*E*) is obtained by calculating the integral of power function towards time as

where *E* is energy, and *P(t)* is power at time *t*. To obtain the energy value of a *P* curve measurement with respect to time, *P(t)* is unidentified and what is identified is the value of power at each particular interval, Eq. (4) is the limit formula to obtain the value of Energy. Eq. (4) is the integration by summation of Eq. (3).

where *E* is energy, *P _{t}* is power at time

where *E _{total}* is total energy,

By inserting Eq. (5) at each measurement, then the result will be E-regular is equal to [E-regular] and E-smart-lighting is equal to [E-smart-lighting].

Eq. (6) shows the calculation for measuring efficiency. Efficiency is the magnitude of the savings gained from the smart lighting system.

where *Efficiency%* is percentage of efficiency, *E _{regular}* is regular energy consumption,

The total power usage for 24 regular hours was 2,827 kWh while power usage after being given treatment with smart lighting is amounted to 2,114 kWh. Thus, there is a saving as big as 25.22%.

Significance testing of the smart lighting systems influence to energy savings has been carried out by using the Wilcoxon statistical test [21,22]. This test is performed on two data sets that are related to each other. These are electricity usage data before and after the smart lighting systems.

Eq. (7) is used to test the significance of smart lighting systems influence against the reduction of electrical power on the experimental results based on Wilcoxon method [23] as follows:

where *Z* is score of significance, *T* is sum of signed rank and *C* is the number of couples with unequal values, with the following statistical hypothesis:

H0: μ1 = μ2 (No influence of smart lighting systems in to changes of electric power consumption)

H1: μ1 ≠ μ2 (There are influences of smart lighting systems in to changes of electric power consumption)

By applying the two-party test of α/2 = 0.05/2 = 0.025, using the function *f(Z)*, then the curve area of *f(Z)* = 0.5 – 0.025 = 0.475 is obtained. Hypothesis rejection H0 is less than -1.96 or more than 1.96. With the value of *Z* = -30.23, then the *Z* position is identified, that is within the H0 rejection area. This test shows that H0 is rejected, so that H1 is being an acceptable alternative. The null hypothesis (H0) is the hypothesis that states the similarities results between the data before and after the treatment. This hypothesis proves that “there is no influence of smart lighting systems to changes in power consumption” while the alternative hypothesis (H1) proves that “there is influences of smart lighting systems against the changes in power consumption”. The test results above indicate a rejection of H0 and acceptance of H1. Thus, it can be clarified that the utilization of smart lighting is influential towards power consumption. The effect is shown by the reduction in power consumption.

We have proposed ILES as an enabler to connect smart lighting applications to various sensors and actuators environment. This proposed system simplifies complexity on developing silo smart lighting applications. We perform some experiments for proving this concept. The results show that the total power consumption of regular system is amounted to 2,827 kWh while using smart lighting system the amount of power consumption is 2,114 kWh. There is a reduction in electric power consumption by an average of 25.22%. Based on a significance test using Wilcoxon method for the changes in power consumption, the Z values obtained under the table, -30.23 and -1.96. It indicates the rejection of H0 and the acceptance of H1. Thus, it is concluded that there are significant influences of proposed system for decreasing power consumption.

The Authors thanks to Telkom University, who supported the funding in the form of International Research Grants with the Decree (No. 130/PNLT3/PPM/2015). In addition, the authors express gratitude to the Digital Service Division (DDS) of PT, Telkom Indonesia and Fraunhofer FOKUS German that has been partners in this study. We also thanks to our colleagues, Mr. Anton Herutomo, Mr. Estananto, Mr. Junharto Halomoan, Mr. Andra Bramansta, and Mr. Dede Suryadi for the support the implementation of the research.

He received the master and doctorate degrees from ITB in 2004 and 2010, respectively. Since 2000, he worked full-time at the Telkom University (aka STT Telkom) as a lecturer and researcher. He has authored over 60 papers published in international journals (e.g., International Journal of Electrical Engineering and Informatics, International Journal Applied Mechanics and Materials, International Journal of Informational and Education Technology) and conference (e.g., International Conference of ICT, International Conference on Computer Engineering and Technology). In the last three year, he received either national or international research grant from Telkom University and Ministry of Higher Education Board. His current research interests are Internet of things, especially in Smartcard technology.

He was born in Jakarta on November 15, 1985. A bachelor graduate of Electrical Engineering ITB in 2003 and master of Microelectronic Mechanical ITB in 2009. The final project, written during his undergraduate is about WiMAX and since then engaged in the development of Broadband Wireless Access (BWA). After WiMAX, the study continued to LTE. LTE was also the topic during his Master’s Thesis. After completion of study and research in the field of BWA he became a lecturer at Telkom University, Bandung. He joined the Scientific Group Telematics and teaches Digital Techniques, Computer Systems and Computer Architecture. His current research topics are in the area of SmartCard and LTE.

He received his bachelor and master degree in Informatics Engineering from Telkom University in 2011 and 2014, respectively. Since 2012, he worked full time lecturer and junior researcher at Telkom University. He was in charge of Network and Operating system Laboratory in the faculty. In the last two years active in some research grant either national or international from Telkom University and also from ministry of higher education of Indonesia. He is also involved in SmartCard Indonesia Consortium in the past 1 year. His current research area covers IoT and M2M communication.

He received bachelor degree in informatics engineering class of 2005, and master degree in Computer Science from Bandung Institute of Technology. He is currently PhD candidate at Institute technology Bandung and also a research fellow with School of Computing, Telkom University. his research interest includes Internet of Things, Avionics and distributed system.

She received her B.E and M.Sc. in Computer Engineering from the College of Industrial Technology-Misurata, Libya and received her Ph.D. degree from the Technische Universitat Berlin, Germany, in 2016. She is currently a lecturer at the College of Industrial Technologies-Misurata, Libya. Her current research interests are in the area of the Internet of Things, smart services and network applications in the Smart Grid power systems. She is an IEEE member.

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