Figure 1. The Scheme of the Streetlight Monitoring and Control System Based on Wireless Sensor Networks (Jing et al., 2010)
Smart cities are urban developments which make use of a variety of Internet of Things (IoT) sensors and Information and Communication Technologies (ICTs) for the collection of data, analysis of that data and finally utilize the findings in the strategic management of assets of the city. Traditionally street lighting systems were used for provision of lighting to communities and on roadways especially for visibility purposes. In recent times street lights have gained new uses which have made it possible for the emergence of smart cities in Caribbean nations. This paper presents a concise review of fifteen (15) intelligent street lighting systems which can provide valuable insights for the upgrading of current cities and boroughs of Caribbean countries into smart cities. At the end of the paper major considerations for the use of street lights in the development of smart cities are discussed.
Widespread use of street lights is attributed to government's utilization of them as a safety measure for the population (George, 2019). After the inception of street lights, evidence disputing their effectiveness has arisen and has led to an academic debate lasting decades with no definitive answer.
Most countries in the world still utilize conventional lighting systems for illumination of streets throughout the country. Presently the lighting systems utilize compact fluorescent lamps (CFL) with a combination of sodium lamps for the provision of illumination. However, these technologies utilize significant amount of energy, hence resulting in wastages in the range of 20-40% of total energy produced (Lohote et al., 2018).
According to Abdullah et al. (2018), the street lights automatically switch on when the environment becomes dark and switch off when brightness appears in the mornings. Significant amounts of energy are wasted, not only because of the inefficient technologies used for street lighting, but also because lights stay on regardless of the presence of moving persons or vehicles along the roadway.
Street light can be adapted to provide benefits beyond just illumination of environs. They can be used to the benefit of national security such as crime detection, weather (Tripathy et al., 2017) and traffic alerting and lots more. This paper reviews fifteen (15) existing street lighting systems/networks and makes recommendations based on notable aspects of their strengths and weaknesses for the development of smart cities and boroughs.
Smart cities exist in the world today and their popularity is rapidly growing with the expansion of the Internet of Things (IoT). This section presents several smart cities around the world which serve to benefit all citizens of the nations they are embedded in.
According to Fair (2018), in 2018 the city of Seattle, United States of America had been rated as the top smart city in the world. Seattle has made enormous contributions towards their development as a smart city. In 2017, Seattle partnered with the University of Washington with the purpose of addressing a variety of urban issues which range from transportation issues, earthquake preparedness and even reduction in carbon emissions in the city (Fair, 2018; Murray & Kubly, 2017). In 2018, Seattle enforced the use of over 800 body camera units by police officers, along with the introduction of an effective gunshot detection system called ShotSpotter to assist police with the determination of where gunshots originated, hence assisting in the solving of crime in the city Fair (2018), Also to be noted, Seattle has implemented a smart park watering system which guarantees the efficient use of water for irrigation of water parks. This minimizes wastage of water in the city (Fair, 2018).
According to Fair (2018), there is an extra 100,000 persons in downtown Seattle during workdays hence resulting in a significant amount of carbon emissions. To this day Seattle has utilized its existing analytics towards the reduction of carbon emissions among over 45% of existing buildings. Through the collaboration between the city of Seattle and the University of Washington, Seattle, has implemented a system called RainWatch which enabled the monitoring of rainfall in real-time and transmits warnings on the possibility of flooding so that citizens are kept aware and safe. Seattle also has developed an adaptive transport management facility which allows traffic lights to be adapted to changing weather and road conditions, towards the benefit of road users (Fair, 2018).
Helsinki, the capital of Finland has piloted smart city initiatives which include smart city innovations that allow the testing of solutions in urban areas (Fagan, 2019). In 2018 Helsinki ranked 2nd in the list of top smart cities in the world. The Smart Kalasatama district of Helsinki is the area where the initiative was launched. The residents of the Smart Kalasatama district, initiate and test smart services and new technology. Some projects include automated garbage collection mechanisms that resulted in a 90% reduction in traffic of garbage trucks. Others included education systems moving away from the conventional methodology to an enquiry-based methodology where hackathons, open data innovations, and even open app competitions are held to boost the education sector (Fagan, 2019).
The spanish city of Barcelona has achieved a large number of benefits via investment in Internet of Things (IoT) for urbanbased systems (Zigurat Global Institute of Technology, 2019). In 2018, Barcelona ranked 4th in the list of top smart cities in the world. Barcelona has implemented the use of LED-type street lights in order to increase energy efficiency, hence leading to reduction in operational costs of the city by at least 30%. Barcelona has also made the inclusion of sensors on street lights to enable the collection of data such as temperature, humidity, noise, presence of human beings, etc. This provides valuable information needed to improve intelligence of smart city systems in Barcelona (Zigurat Global Institute of Technology, 2019).
Barcelona has implemented the use of smart bins which suck waste into underground storage facilities to help reduce noise pollution caused by previously used collection vehicles, and also reduce the smell of garbage which awaits collection under conventional systems. These smart bins also keep track of the amount of garbage collected daily, hence allowing the city to plan better its allocation of resources for collection of garbage. Finally, the collected waste is incinerated in order to produce energy for heating systems (Zigurat Global Institute of Technology, 2019). Bacelona has also implemented the use of ground sensors which are able to stream real-time data on the temperature, humidity, atmospheric pressure, wind velocity and sunlight, hence providing farmers with valuable information for guiding their decisions in scheduling crop production activities such as irrigation, and as a consequence avoiding issues such as overirrigation (Zigurat Global Institute of Technology, 2019).
In 2018, Singapore ranked 5 in the list of top smart cities in the world and also was awarded the City Award in the Smart City Expo World Congress of 2018 (Zoria, 2019; Yee, 2019). Singapore's goal is to have a digital society, government and economy. In 2019, Singapore spent approximately 1 billion USD in the execution of its smart city initiative called Smart Nation (Zoria, 2019). Smart Nation enables the utilization of digital technology and innovation in Singapore to the drive of liveability and sustainability in the nation. Smart Nation collects and collates data received from sensors which have been placed all around the city and as a consequence a 3-dimenstional (3D) model of the city (referred to as Virtual Singapore) allows planners of the city to analyze traffic and pedestrian flows, allows them the opportunity to test a variety of city concepts and thereafter execute crowd evacuation simulations to be incorporated in emergency training (Zoria, 2019). It is important to note that Singapore has been using its streets for trials of robotic buses, self-driving shuttles and autonomous taxis. It is expected by the end of 2020 that all vehicles within the city will be fitted with satellite navigation units, hence providing the Smart Nation platform an abundance of data for analysis and use in the monitoring of traffic to eliminate congestion issues (Zoria, 2019).
What is common among all the smart cities reviewed in this section of the paper is the need for collection and analysis of data collected by sensors in the cities to better guide decisions to be made in the city management execises. The use of street lights as a platform for installation of sensors needed to collect data seems common and apparent. The subsequent section of this paper will provide a concise review of several intelligent street lighting systems that can pave the way for the development of smart cities in the Caribbean, somewhat like the smart cities featured in this section of the paper.
Jing et al. (2010), presented a street light monitoring and control mechanism which was based on the wireless sensor network (WSN) architecture. Features of the system such as manual deployment of nodes, node obstructions, clustering of nodes, and energy unlimited were also focused on. A geographical routing strategy based on location information for nodes and remote terminal units (RTUs) was developed (Jing et al., 2010). Jing et al. (2010), also focused on improvements on node forwarding approaches utilized in flooding.
The street light monitoring and control mechanism developed by Jing et al. (2010), was based on a WSN which includes wireless sensor nodes and control center RTUs as shown in Figure 1. The computer application found on the central computer monitors that controls the street lighting system and consist of features geographical maps, system topology, audible and visual alert capabilities, ability to forward alert messages to mobile phones, etc., (Jing et al., 2010). RTUs found at each streetlight power substation monitor and control sensor nodes within its coverage area, communicate with control centers using GPRS communication networks, and finally store the data derived. RTUs are also responsible for the gathering of information about the individual lamp status on/off, voltages and currents in the power lines, and finally they are capable of processing and transmitting data to control centers (Jing et al., 2010).
Figure 1. The Scheme of the Streetlight Monitoring and Control System Based on Wireless Sensor Networks (Jing et al., 2010)
Sensor nodes for the system are installed poles containing street lamps. Also clusters (sensor nodes powered by the same power substation) of sensor nodes are established. Clusters exist and consist of sensor nodes powered by the same power substation. Multi-hop routing protocol is used to minimize the limitation of the sensor node communication by building obstruction. In multi-hop wireless networks one or more intermediate nodes exist and receive forward packets via wireless links (Jing et al., 2010). The main purpose of WSNs have several functions - derive and process data from street lighting systems, give control to street lighting operation and transmit data back to control center on the actual street lighting operations. Many times development of efficient routing protocols are needed to guarantee the task of routing between sensor nodes and RTUs are established efficiently. As such Jing et al. (2010), presented the development of a geographical routing scheme which utilized location information instead of network addresses for formulation of more efficient routing between street lighting nodes and the central processing terminal. Location information is not sent to designated regions or even the nearest node, but rather to all neighbours.
Srivatsa et al. (2013) presented the control of the intensity of street lights between time intervals 11.30 PM and 5.00 AM, while at the same time detecting the movement of cars and human being on the road - increasing the intensity of the street lights when this movement is detected and reducing it when the movement is passed (Figure 2). The proposed system developed by Srivatsa et al. (2013) utilized laser gates at each street lamp post and at a height of 2 ft above the ground to detect movement of objects on the road between the hours of 11.30 PM and 5 AM, hence making particular lights go full intensity to give light to travellers. This results in the reduction of power consumption along with the provision of lights for use by late travellers (Srivatsa et al., 2013).
Figure 2. Placement of Laser Gates in Smart Street Light System (Srivatsa et al., 2013)
Yusoff et al. (2013) presented preliminary study for the development of a smart street lighting system for the Malaysian area. The system of Yusoff et al. (2013), made use of the concept of Wireless Sensor Networks for development and also made use of Waspmote as a sensor node, the computer and Meshlium gateway as a server. Information on the running status of the street light along with the amount of energy utilized was monitored using the senor node. Yusoff et al. (2013) achieved best results by splitting the project into several parts - site planning, hardware development, sensor node communication and sensor node operation. For the study Yusoff et al. (2013) utilized LED type street lights because it was realized that standard incandescent lamps could not be dimmed (which was important for the study) and consumed a large amount of energy when compared to LED type lamps. At the end of the project Yusoff et al. (2013) concluded that the street lighting system developed saved energy via the approach of controlling the light intensity of the lamp with the method of Pulse Width Modulation. Yusoff et al. (2013) also indicated that an improvement in maintenance operations can be derived without need for roved inspection. Despite the benefits of the system, Yusoff et al. (2013) highlighted some drawbacks, one being that the power saving benefit will not be consistent from area to area – cities and towns with high activity will utilize much more power than remote areas with low activity.
Lavric et al. (2014) presented on the field testing of a street lighting/monitoring and control system based on a WSN network which enabled remote controlling of street lamps. The system of Lavric et al. (2014) incorporated the use of Doppler sensors which allows detection of approaching vehicles. When vehicles were detected the intensity of the street lamp lighting increases to ensure road safety is maximized. On the other hand, when vehicles were not present the street lamp intensity decreased. The system of Lavric et al. (2014) also included current sensors to ensure possible malfunctions were identified and so that maintenance operations could be easily facilitated. Lavric et al. (2014) indicated that results obtained gave way to the integration of the system into the smart city concept. Lavric et al. (2014) also indicated that suggested system can result in significant reduction in energy consumption costs as well as maintenance costs. Sensory information about vehicle detection were also obtained which allowed for improved scheduling of maintenance activities (schedule maintenance when less traffic present) (Lavric et al., 2014).
Zalewski (2016) presented the development of a concurrent lighting system for interactively controlling street lamps which were located along a selected road in Poznań. The light spots of Zalewski (2016) were switched on/off depending on the needs of the users present in the environ of the street lamps (Figure 3). The approach of Zalewski (2016) conserved energy by switching off street lights that are not in immediate use by anyone. The system was put into operation for over a year and evaluated from a perspective of economics. It was realized that utilization of the system of Zalewski (2016) resulted in significant reduction of power consumption when compared to traditional street lighting systems.
Figure 3. Idea of Luminaires Switching on and off (Zalewski, 2016)
Ke and Xiao (2016) presented the development of a wireless network of street lights using ZigBee. The system collected a variety of street lighting data such as current, voltage and light intensity, and transmited the data to a monitoring terminal for analysis and storage purposes. Ke and Xiao (2016) utilized the analyzed data for achieving automatic adjustment of the brightness of the street lamps depending on the value of the light intensity sensor. The system accommodates 255 ZigBee nodes - 255 street lamps. Experimental results of Ke and Xiao (2016) indicated that the proposed method resulted in significant power savings compared to conventional approaches.
Yussoff and Samad (2016) presented the development of a low-cost sensor node for street lighting which is responsible for sensing and detecting the motion of a car or any object in the vicinity of the street lamp. When an object or car is sensed moving past the street light, the light will be switched on and will transmit data to another street lighting pole, hence resulting in it possibly being switched on afterwards (Yussoff and Samad, 2016). When no object or car is sensed the steep light remains off. Yussoff and Samad (2016) indicated that the use of this system will result in significant reduction in power consumption compared to the conventional street lighting systems where the lights are keep on the entire night.
Bhairi et al. (2017) proposed a smart energy efficient street lighting system using low cost microcontroller based Arduino. The objective of the system was for energy conservation of street lights found in rural and urban systems all towards the goal of fostering smart cities. The system of Bhairi et al. (2017) consisted of LED driver, LED luminaire, PV panel, motion sensor, charge controller light sensor, and the microcontroller based on the Arduino. The street lighting system utilized solar technology to further reduce costs due to power consumption. Another major feature of this system is that it is controlled based on traffic in the vicinity of the street lights (Bhairi et al., 2017). Bhairi et al. (2017) concluded that the use of this system resulted in a power saving of 70-80% compared to the conventional systems.
Abinaya et al. (2017) discussed the development of street lighting system for smart and weather adaptive illumination of surrounding areas. The system contained a camera on the street light for tracking actions performed on the road (Abinaya et al., 2017). A panic button is also included in the system, in the event someone is in danger they can utilize it for alerting the nearest police station. All street lights were connected to the nearest police station and each has a cloud accessible account to allow access to footage of the incident locations. Abinaya et al. (2017) indicated that the developed system assisted in both energy wastage as well as crime detection. Abinaya et al. (2017) also indicated that the cost of energy was reduced by 50-60% compared to the conventional systems.
Manitha et al. (2017) proposed an intelligent street lighting with goals to optimize energy consumed by street light via introduction of smart solar street lights, as well as enhance safety on the road, hence optimizing fuel consumption (Figure 4). Piezo sensors were utilized for detection of the velocity of vehicles, which resulted in actuation of speed breakers. LEDs were utilized for street lighting and were powered by batteries powered by solar panels (Manitha et al., 2017). Controller units were installed to monitor the charging of batteries, hence avoiding them from being overcharged. The system operated as follows – the LEDS are turned on when darkness is sensed by the LDR and glows at 25% of maximum intensity. However, the LEDs were turned off if light is sensed by the LDR. On the other hand, when the speed limit was exceeded the microcontroller increased the intensity of the LEDs to 100% (Manitha et. al., 2017).
Figure 4. Car Passing Through Speed Breaker (Manitha et al., 2017)
Widodo et al. (2017) discussed the development of a smart street lighting system using M2M technology which enabled the communication between all devices and users within the street lighting area (Figure 5). The system of Widodo et al. (2017) also guaranteed less delay, congestion and communication errors. LED lamps with high dynamic level of illumination were used in the system developed and intelligence was added to ensure that they can independently perform control operations (Widodo et al., 2017). As a result, the system was able to perform functions such as light dimming (Knobloch, 2015), power saving, defect detection as well as daily power consumption reporting to the central monitoring and control terminal. The needs of users around the street lighting system of Widodo et al. (2017) determined if there are 100% illuminations, 0% or if the lights must be dimmed. According to Widodo et al. (2017) the system has high capability for power savings compared to convention street lighting systems.
Figure 5. Proposed Architecture of Smart Street Lighting System (Widodo et al., 2017)
Abdullah et al. (2018) presented the development of a street light controller system capable of resulting in reduced power consumption when compared to the convention street lighting system (Figure 6). The system of Abdullah et al. (2018) utilized an Infrared sensor (IR), Light Dependent Resistor (LDR), LED and battery. All parts of the system were controlled by an Arduino UNO. The velocity of objects in the vicinity such as cyclist, pedestrians and vehicles determines the amount of dimming that occurs in the street lamps. The greater the velocity of the objects, the greater the intensity of the illumination of the street lamp (Abdullah et al., 2018). Abdullah et al. (2018)however indicated that the velocity of the objects is utilized for calculation of the level of dimming of the street lamps.
Figure 6. Different Settings for Different Objects (Abdullah et al., 2018)
Bhosale and Ankalkote (2018) presented a remote street light system which consists of intensity control based on movement of vehicles, climatic and weather conditions such as rainy weather, humidity, etc. The system is based on LEDs and wireless sensors network such as the zigbee. The system of Bhosale and Ankalkote (2018) automatically controls street lights based on seasonal variations, etc and results in large power savings. The system makes use of LEDs because they have a much longer lifespan than other types of lamps., as well higher efficiency and reliability (Bhosale and Ankalkote, 2018). The system is equipped with LDR sensors for night detection and other sensors such as temperature sensors or even humidly sensors for activating the street lamps.
Lohote et al. (2018) presented an energy efficient street lighting system which also provides additional benefits such as emergency lighting, intensity variant lighting, maintenance alerting system and flood monitoring (Figure 7). The system of Lohote et al. (2018) achieved energy efficiency by allowing all lights to glow with intensity as required by its surroundings. The LEDs are controlled by a Light Dependent Resister (LDR) and, the intensity of the light will be controlled by whether conditions experienced. Although street lights were used primarily for provision of illumination of areas, in the system of Lohote et al. (2018) they are also used for the detection of water levels during rainy seasons simply by the addition of ultrasonic sensors to the street lighting pole. Once water levels rise above certain levels, notifications will be sent to a control center using ESP8266 WiFi for remedial actions. The system of Lohote et al. (2018) will also display weather and vehicular accident alerts on LCD displays placed on street lamp poles.
Figure 7. Light Coverage when (a) Pedestrians/Vehicles crossing the street lights (b) Vehicles Parking in Close Proximity to Light (Mary et al., 2018)
Mary et al. (2018) indicated that the conventional street lighting system consumed a significant amount of power because they were conditionally switched on and stay on from the advent of evening to just before the rising of the sun in the morning. The system proposed by Mary et al. (2018) consisted of controllers and sensory components with added intelligence to the system. Using these components, it was able to automatically switch on street lights when people and vehicles were sensed around the street light pole (if motion detected), dim when demands for street lighting have decreased, and switches it off when there were no persons or cars present (Mary et al., 2018). When motion was detected, the individual street lighting modules sent messages to the other units, hence making it possible for all street lights in the area to be turned on before pedestrians noticed (Mary et al., 2018). As a result of the switching on/off and dimming operation the power consumption is minimized, hence making it more energy efficient compared to the conventional street lighting systems (Mary et al., 2018). Mary et al. (2018) indicated that the use of the proposed system resulted in a 35% reduction in cost of energy by progressive dimming and also indicated that the power consumption could be further reduced by 42% if proper maintenance is exercised.
All of the street lighting systems reviewed provide valuable features that will benefit citizens of any nation willing to incorporate them in their city networks. The ultimate undertaking is the development of smart cities in Caribbean nations via the engineering of intelligent street lighting networks which are capable of:
The purpose of this section is to identify notable considerations required for the development of smart cities in the Caribbean utilizing intelligent street lighting networks. As such street lights will play a very important role in gathering of intelligence for the birth of these smart cities. Most considerations made are guided by the scientific thought and evidence. The following are crucial considerations:
Most of the street lighting systems reviewed in this paper provided the benefit of smart illumination, hence resulting in a reduction of power utilization compared to if lights remain on throughout the night time. This power saving translates to savings in the cost of operating the street lights at the unit level, and if considered at a national level this is a significant reduction in the cost of power to operate all lights in the country. Although smart illumination minimizes the consumption of power, some would argue that it can possibly encourage an increase in crime because of the reduction in the time that lights are switched off because of non-detection of moving elements. Furthermore, many of these systems are set up to detect movement rather than the presence of a living object within the detection range of the street light. As some of these existing systems may provide conditions conducive to criminal activities in the event criminals decided to wait motionlessly in the dark for an innocent bystander. As such there is a need to not only consider motion detection in smart illumination but also some methodology to detect the presence of living human beings within the detection range of the street light, hence resulting street lights being kept on once a living object is detected, despite lack of movement.
Some systems such as those developed in Jing et al. (2010) and Lavric et al. (2014) provided benefits of smart maintenance and maintenance scheduling. Data transmitted on the running status of the street lamps along with traffic density may be transmitted to an administrator for use in actioning maintenance works. Some may attempt to utilize this feature for single maintenance purposes, hence at the instant that a street light malfunctions maintenance is conducted on the light soon after. Although this feature is an advantageous one it is probably a costly one. It may be a better idea (as may be the case already) to schedule maintenance activities on a batch basis, in districts. Hence providing the energy company an opportunity to optimize the cost of maintenance works. Maintenance on a lamp by lamp basis may increase the overall cost of maintenance per annum. Therefore, another major consideration is investment in an optimum maintenance strategy for street lights to optimize cost of maintenance.
Of the systems reviewed in this paper, none have made use of the street lighting networks for solving gun-related crimes. This should be a major consideration. The placement of an abundance of acoustic sensors in districts which allows the police service an avenue for determination of the precise location of the origin of gunrelated activities is a worthwhile consideration.
When a gunshot is made a supersonic waveform results which approaches acoustic sensors at different times because of the difference in distances of these sensors from the origin of the supersonic wave. The coordinates of the origin of the gunshot are determined by selecting three acoustic sensors that have detected the supersonic wave, and performing 3D triangulation. Once vehicles utilized by police officers on patrol contain Global Positioning System (GPS) it is very possible for the coordinates of the origin of the gunshot to be relayed to the nearest police officers on patrol to the coordinates of the gunshots, for use in their investigation.
Incandescent street lights are still used in many parts of the world despite them having high power consumption ratings. Several of the street lighting systems reviewed in this paper utilize LEDs in their street lighting networks and reported a significant reduction in power consumption by their systems compared to when standard incandescent street lamps (Abdullah et al., 2018; Bhairi et al., 2017; Manitha et al., 2017; Yusoff et al., 2013). It is a great consideration for LED-type street lights to be utilized instead of incandescent street lights simply because they serve to reduce the power consumption of the street lighting network, and as a consequence reduce the demand on the grid.
The planet Earth receives solar energy in form of what we call solar radiation. The amount of radiation reaching any location of the earth depends on factors such geographic location, season, time of day and local weather. According to Rajput (2017), the majority of India receives approximately 4-7 kWh of solar radiation per square metre every day (more than 5000 trillion kWh per annum). The sun is an abundant natural source of energy and current street lighting networks should take advantage of this in the powering of street lights. Several of the street lighting systems reviewed such as Bhairi et al. (2017) and Manitha et al. (2017) incorporated solar powering to reduce power demand on the grid. The use of solar powering techniques is therefore a good consideration for the development of intelligent street lighting systems involved in the emergence of smart cities.
Of the systems reviewed in this paper, none have reiterated the need for ensuring their systems tamperproof to guarantee optimum functionality. Because of the existence of criminal elements, it is possible that these intelligent street lighting networks be tampered with to benefit the needs of criminal elements. Even if the systems cannot be made tamperproof the tampering of these devices should be made illegal. As such the placement of these intelligent street lighting systems should be supported by the constitution of such nations, appropriate legislation must be enforced, and anyone caught tampering with these units must be fined/penalized. This will deter tampering activities as a consequence.
Many of the systems reviewed such as (Ke & Xiao, 2016; Lavric et al., 2014; Mary et al., 2018) utilized wireless sensor networks in their operations. Providing nationwide coverage and the support of all possible features such as supersonic wave detection, smart illumination, weather detection, even transmission of images to support enforcement of the law and more will result in an increase in data transmission over wireless networks. Although no study conclusively proves wireless networks negatively affects public health, it is a good consideration to evaluate the possible impact on public health of increasing data transmission via smart cities, just in case there is merit in such study.
In the case of national security, it is expected that the advent of intelligent street lighting networks can positively affect the detection of and deterrence from criminal activities, however this can only be verified after implementation of the networks and the monitoring of the level of criminal activities occurring after implementation over a period of time, in comparison to before.
Implementing the intelligent street lighting network will involve high capital expenditure and it would be unfortunate to make such an investment and realize that it failed to impact on deterring criminal activities. As such it is a valuable consideration to implement the intelligent street lighting networks on a city-by-city basis, starting with the cities where criminal activities are highest. After implementing it in one city a study must be conducted to determine if the presence of such networks did impact crime in that city. If the research proves to be conclusive and does suggest a positive effect on crime reduction, then the network should be extended to other cities using the same approach and gathering new information to support the decisions made.
The development of smart cities is indeed very important to the future of Caribbean nations, as they bring forward many benefits which have implications on the reduction of operational expenses of the nations that host them. This paper presented a concise review of fifteen (15) intelligent street lighting systems which can provide valuable insights for the upgrading of current cities and boroughs of Caribbean countries into smart cities. The paper also presented major considerations for the use of street lights in the development of smart cities. The information presented in this paper can now be utilized as a guide for the incorporation of smart cities into the culture of Caribbean nations.
The author would like to thank the organizers, staff and most importantly the audience of the 2020 Smart Technologies for Sustainable Development (STSD-2020A) symposium for their valuable opinions and discussions which have served as valuable contributions to this paper.