**3.1 Survey and problem definition**

Various road classifications are existed in terms of traffic flow. Principal arterials, minor arterials, rural collectors, local roads and very low-volume roads. The last is what our concern in this section. Statistically, for low-traffic roads the flow rate of the vehicles is assumed to be 400 vehicles per day [14]. In these roads, even simple lighting system is not installed mostly, and authorities rely on vehicle lights to illuminate the roads, which putting people life and valuable product passing in these roads under the risk. The main reason of non-lighting system is the desired of saving electrical energy. The main reason of non-lighting system is the desired of saving electrical energy. However, continuously lightened fully roads cause wastage of electricity, as only one vehicles may appear every three or four hours and even more during the night time. Each of these two scenarios are contradicting and are extremely significant issues.

Several researchers did some projects and published their work related to this topic, however, none of them has considered the lighting automation system on low traffic road. Articles are mainly related to smart or automated main street lighting systems or parking areas. In the following paragraphs, several researches' results is discussed, and main points are drawn into attention.

Some studies proposed a suggestion to use two sensors in order to consume less power with maximized efficiency of a system [15]. Light Dependent Resistor (LDR) sensor is utilized to measure the sun light intensity to control the switching action of LED streetlights, and Passive Infrared Resistor (PIR) motion sensor is used for changing the intensity of LED light when there is no motion of object in the street at mid-night, then all the streetlights are dimmed. However, [16] indicates that LDR and PIR sensor are used for same purpose, but without dimming the light, just switched on or off. In [17], the author worked on this topic using Infrared Resistor (IR) sensors which measure the heat of an object as well as detects the motion, in contrast to previous researchers did. They developed the system using Arduino Uno R3 while [18] achieved the same by Raspberry Pi 3 micro controller.

Another research effort offered Zigbee Based Smart Street Light Control System Using LabVIEW. Here, movement is detected by motion sensors, communication between lights is enabled by Zigbee technology. So, when a passer-by is detected by a motion sensor, it will communicate this to neighboring streetlights, which will brighten so that people are always surrounded by a safe circle of light [19].

Another author developed Intelligent Street Lighting System Using GSM technology. The aim is to achieve the energy saving and autonomous operation on economical affordable for the streets by installing chips on the lights. These chips consist of a micro-controller along with various sensors like CO2 sensor, fog sensor, light intensity sensor, noise sensor and GSM modules for wireless data transmission and reception between concentrator and PC. The emissions in the atmospheres would be detected along with the consumption of energy and any theft of electricity [20].

Automatic street-light control system using wireless sensor networks is also proposed in some design. The system contains lamp station and base station [21]. Each lamp station consists of Arduino Uno board as microcontroller, PIR sensor, emergency switch, LDR sensor, nRF24L01 transceiver, ultrasonic sensor, relay, LED light and a solar panel as energy source. The base station consists of Raspberry Pi as processor, nRF24L01 transceiver, and a GSM module. The automatic

streetlight turns on under three conditions. Firstly, when PIR sensor detects a human or a moving object vehicle LED light is turned on. Secondly, an ultrasonic sensor is used to detect distance objects and turn on the light accordingly. Lastly, a switch is included for manual operation in case of maintenance work. The LDR sensor is included to measure the light intensity for identification of the day and night. There nRF24L01 wireless transceiver transmits the sensor information and the light status to the Raspberry web server to upload on the web page. Also, it receives commands sent from the web page to turn on or off the light at a particular node. The entire system is powered using solar cells making it more energy efficient.

**3.2 System design description**

*Economic Applications for LED Lights in Industrial Sectors*

*DOI: http://dx.doi.org/10.5772/intechopen.95412*

straight spans and roundabout.

**Figure 2.**

**33**

*Automatic lighting system schematic.*

*3.2.1 Lighting control conceptual design*

Lighting automation system in low traffic roads is intended to implement in the illuminated roads. It is supposed to have source power supply, feeder pillar with controller, light poles with day/night sensor. Such conventional system can be upgraded by new automated system. The methodology of lighting automation system in low traffic roads is achieved by applying the moving object recognition technique using cameras. Firstly, the road is sectionalized into several zones. Each zone depends on how much distance is existed between two feeder pillars, typically 400 meters. So, light poles in each zone will be switch on/off together. It means that each zone will have its feeder pillar (control panel) with controller, day/night sensor, motion sensor, and camera. Night vision cameras are installed on the road in such way to detect the vehicle arrival-to and departure-from each zone. The controller is designed to illuminate only the zones in which the vehicle is detected. The type and span of the zone are calculated based on the road design considering

The control scheme of the automatic lighting system is illustrated in **Figure 2**. Day/night switch detects darkness status to start the controller and hence motion sensor and night vision cameras. Now, let us consider that there are two adjacent zones (Zone N) and (Zone N + 1), and vehicle enters to Zone (N + 1). Mainly, day/ night sensor and motion sensors of (Zone N + 1) need to be installed before the camera of (Zone N + 1), while camera of (Zone N + 1) need to be installed in (Zone N) near to the end. This is because camera need to start capture the moving objects images only after motion sensor detects any object in advance and sends the signal to the camera to start operation, and hence the controller takes the proper decision

For that, camera is installed on a light pole about 80 m before each zone. This distance provides approximately 2 seconds for data processing and control assuming maximum speed is approximately 60 km/hour. **Figure 3** illustrates the installation location of (Zone N + 1) camera, day/night sensor and motion sensors in (Zone N). The software in the controller extracts the image from the camera and analyze it to determine whether the object is vehicle or not. If the object is not a vehicle, no action is taken by controller. In case the object is vehicle, signal shall be sent to Zone N + 1 lighting feeder pillar to switch on light of Zone N + 1 Simultaneously signal

for switch the light of (Zone N + 1) before the object enter the zone.

shall be sent to Zone N controller to switch off lightning system of Zone.

The problem of high operational cost of low traffic light that use HPS lighting is partially solve by using LED light fitting instead of HPS luminaries [10].

Many real projects and researches have been done on this area [22–24], but few of them are focused in this topic exactly. Most of them consider street, campus, parking, park or any small area lighting system. The rest of them is devoted to road light and control systems. Brief analysis, discussion and comparison will be introduced hereinafter.

From the above literature review, firstly, all systems mentioned above used LDR sensor to sense night-time to operate the control system itself. In the system prosed in this Section, the same day/night sensor idea is also use to know exact hours of night-time or any dark time during the day time due to heavy cloud or any other reasons.

Secondly, all systems above have used motion sensors to detect the object movement whatever this object is, even if it is not vehicle, and hence control the lights in terms of switching ON/OFF or dimming. IR sensors and PIR sensor were the preferred sensors used to detect the object. These type of sensors detect mainly warm object and their movement. But, for the suggested system in this Section that need to be used for low traffic road, movement of only vehicle is needed to be recognized and hence switch on the light or dim them. The proposed system need to be designed to avoid any other motion such as animals, birds, or other objects which may be detected by IR or PIR sensors as this unnecessary detection of motion can cause unjustified energy consumption. Therefore, it is needed to give new approach to tackle with such problems. New approach could be to add the night vision smart camera to the system in order to recognize only the vehicles among all other objects that the camera detects.

Thirdly, some systems control the illumination by measuring the intensity of the objects movement and change the dimming of the lights accordingly. But for illumination system of low traffic roads, the intensity of the vehicles is continuously very low, and hence dimming technique is not effective solution.

Fourth, using LED light continuously operate during the night for low traffic roads can reduce the cost of illuminating the road compared with any other HID lighting, but still this is not best solution because the utilization of this system by this operational philosophy is not an efficient utilization because most of the time the light is ON unnecessary.

Fifth, in general, previous researches have been done on lighting automation system for the roads which serve both pedestrians and vehicles. But, this Section tries to design automation lighting system for long road with low traffic, where no need to switch on the lights for movement of any object except the vehicles.

In this section, efficient, safe and cost effective solution to design automated lighting system suitable for long roads with low-traffic is provided. First, description of the entire system design is discussed. Then, methodology and the programing of vehicles recognition using camera images are illustrated. Economic analysis for the proposed system is carried out. Finally, conclusion is given.
