Artificial Neural Network based Smart and Energy Efficient Street Lighting System: A Case Study for Residential area in Hosur

Mohandas, Prabu; Dhanaraj, Jerline Sheebha Anni; Gao, Xiao‐Zhi

doi:10.1016/j.scs.2019.101499

Cited by 78 publications

(36 citation statements)

References 20 publications

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“…Lobaccaro et al, 2019). Recharging the PV batteries for LED streetlamps to 100% requires about 9-10 hours which makes them economically viable (Filimonova, Barbasova, & Shnayder, 2017;Mohandas, Anni, & Gao, 2019). Our data one light come from the Timebie (2019) and include the accurate logs of sunrise sunset daylight hours in various world's destinations (in fact yielding sunrise and sunset times around the world).…”

Section: Empirical Model Of Economic and Energy Efficiencymentioning

confidence: 99%

Economic efficiency and energy security of smart cities

Strielkowski

Veinbender

Tvaronavičienė

et al. 2020

Economic Research-Ekonomska Istraživanja

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The aim of this paper is to provide an analysis of the determinants of economic efficiency and to assess the prerequisites for the energy security of smart cities. The main methods of the paper include an economic analysis of the infrastructure improvements that result in reducing the energy demand of the smart cities represented by the intelligent light-emitting diode (LED) street lighting system. Smart LED streetlights are getting increasingly popular in the world's major metropolises as one of the leading components of the "smart" city. We compare the efficiency of LED street lighting used in smart cities with a commonly used lighting system based on sodium lamps. Our results demonstrate that LED street lighting system can significantly reduce the energy demand of any modern city. Moreover, we show that smart grids might help distribution systems within smart cities to better integrate intermittent renewable energy sources such as wind and solar. The main research novelty of our study compared to previous studies from the literature is the estimation of net profit (NP), Net Discounted Savings (NDS), as well as the total savings (TS) using the example of an average European metropolis. Our findings show that there is a need for better management including strong networks of leaders to drive smart city policies and investments and to cover wider city areas with economically sustainable projects and plans. In addition, our findings yield that smart city projects should aim at finding solution for smart connected local energy storage systems to support more renewable energy sources on the power grids. Our results might be of a special interest for city planners, local government stakeholders, as well as urban policy makers dealing with planning and managing smart cities.

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Section: Empirical Model Of Economic and Energy Efficiencymentioning

confidence: 99%

Economic efficiency and energy security of smart cities

Strielkowski

Veinbender

Tvaronavičienė

et al. 2020

Economic Research-Ekonomska Istraživanja

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“…The reduction of this energy utilization is not easy. Along with the help of different computing mechanisms, this power utilization could be lessened (1) . In any country, street lighting plays a significant role in the contribution of pedestrian and traffic safety.…”

Section: Introductionmentioning

confidence: 99%

Cloud-based energy efficient smart street lighting system

Umar¹,

Gill²,

Shaikh³

et al. 2020

IJST

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Background/Objectives: Pakistan is experiencing significant energy crises for the last two decades. The increasing power demand cannot be controlled with traditional energy techniques. The conventional street lighting system remains ON all over the night. Consequently, a huge amount of energy is wasted. To overcome the shortage of energy, an efficient smart lighting system is proposed. Methods: The prime thought to accomplish is``Energy on-demand'' i.e. handed-in wherever, whenever required. To achieve this goal, the cloudbased smart street lighting system provides a feasible solution. The proposed system uses an Arduino and its various shields based on a movement-based actuation system like Light Detection and Ranging (LiDAR), automate the street lighting system. This design is executed and implemented on a one-way road and its results are carried out at three different scenario cases. The analysis is done by a decision-making module that obtains results from the sensor (LiDAR). Findings: The availability of low cost advanced devices like LiDAR, Arduino, cloud storage, and the accessibility of wired and wireless connection, smart street lighting system becomes a reality. The proposed system is beneficial to overcome the CO 2 emission. Further, it will also be helpful to avoid the unnecessary consumption of streetlight as well as to reduce power utilization and save energy up to 99%. Applications: This proposed framework has an immense potential to revolutionize street lighting and to achieve the demand for a smart street lighting system that is easy to maintain, durable, and reliable.

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“…The costs of energy will shoot-up at the rate of the demand. The major problem at present irrespective of size of country is revenue loss incurred due to energy wastage in street lighting systems [1]. It is affecting country's economy.…”

Section: Introductionmentioning

confidence: 99%

“…In the urban centers, the most challenging issue is with the energy management because of their complexity and their pivotal role [2]. The street lightings are provided to offer safe and comfortable environment for drivers and pedestrians during night and foggy weather [1], [2]. However, at present, street/compound lamps are found to be illumined at all times irrespective of time and presence or absence of pedestrian or vehicle movement.…”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the lamps are found to be illuminated with full brightness at midnight or even in daylight most of the times [7]. Although, completely resolving energy wastage is not easy [1], it can be minimized to certain extent by employing so called efficient and smart lighting system [8]. The efficiency can be achieved by replacing conventional incandescent and fluorescent lamps by LEDs, and the lightings can be retrofitted to make smart by providing automatic monitoring and control algorithm.…”

Section: Introductionmentioning

confidence: 99%

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Smart Street Lighting Detecting Vehicle and Pedestrian Movement Aiming for Sustainable Bhutan

Karchung,

Tenzin,

Tenzin

et al. 2020

IJEAT

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An energy crisis is global issue nowadays. Bhutan however, does not realize it being blessed with good geographical and demographical diversity. It is high time that Bhutan realize the need of energy conservation technique. The electrical energy is wasted unnecessarily which starts from keeping the mobile charger plugged in the socket when not in use to lamps keeping ON in streets throughout day and night. People don’t seem to care but monitoring it for better conservation benefit has become crucial in underdeveloped countries like Bhutan whose source of energy is limited to hydropower only. Wind and solar generations are feasible but the energy cost per unit would be very high due to high initial cost. A case study conducted within the college campus revealed tremendous savings a college can make just by replacing conventional compact fluorescent lamp (CFL) with light emitting diode (LED). Therefore, the best option for Bhutan and Bhutanese people is to take better care of the existing energy sources and use it judiciously. This paper proposes a method to monitor and control the street/compound lighting in a smarter way. The two types of sensors are employed. The light dependent resistor (LDR) is used to monitor the intensity or brightness of surrounding and passive infrared (PIR) sensor is employed for detecting infrared source. The sensor output is processed and monitored by the PIC16F877A microcontroller. Moreover, the incandescent lamp and the compact fluorescent lamp will be replaced by LED lamps. The project aims to reduce power consumption in Bhutan through proposer control of street/compound lighting so as to have better economy of the country by exporting more unit of energy to neighboring country.

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Artificial Neural Network based Smart and Energy Efficient Street Lighting System: A Case Study for Residential area in Hosur

Cited by 78 publications

References 20 publications

Economic efficiency and energy security of smart cities

Economic efficiency and energy security of smart cities

Cloud-based energy efficient smart street lighting system

Smart Street Lighting Detecting Vehicle and Pedestrian Movement Aiming for Sustainable Bhutan

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