Internet of Things (IoT) is changing the world by connecting billions of physical and virtual objects with distinctive identities to the Internet. This fusion results in generating huge volumes of data that might not be manageable using today's storage and data analytics technologies. Although cloud computing offers services to tackle this issue at infrastructural level, its efficiency for time sensitive applications (e.g. oil, gas, and traffic monitoring) is still questionable. Arguably, transferring massive amount of data to the cloud for storage and processing may lead to cloud overloading and saturation of network bandwidth. In this study, an integrated fog and cloud computing framework is introduced to overcome the limitations of real-time analytics, latency and network congestion of basic cloud services for traffic monitoring. The proposed approach is implemented to prototype a smart traffic monitoring system (STMS). The proposed monitoring system is designed for congestion monitoring and traffic light management. It can also be tuned to detect traffic incidents that requires immediate assistance during congestion. In this framework, a tiny computer-on-module serves as a fog node to collect real-time data from geographically distributed sensors and to transfer it to the cloud for storage and processing. The results show the efficiency of the fog network in improving the performance of the cloud platform in terms of reducing the response time and increasing the bandwidth. Furthermore, the proposed integrated fog and cloud framework is interfaced with Tweeter to send alerts about traffic congestion to be subscribed users in the form of Tweet messages .

Internet of things-based fog and cloud computing technology for smart traffic monitoring

IoT for energy efficient green highway lighting systems: Challenges and issues

This project aims for designing and executing the advanced development in embedded systems for energy saving of street lights. Currently, we have a manual system where the street lights will be switched ON in the evening before the sunsets and they are switched OFF in the next day morning after there is sufficient light on the outside[1]. But the actual timing for these lights to be switched ON is when there is absolute darkness. With this, the power will be wasted up to some extent. This project gives solution for electrical power wastage [2]. Also, the manual operation of the lighting system is completely eliminated. The proposed system provides a solution for energy saving. This is achieved by sensing and approaching a vehicle using an IR transmitter and IR Receiver couple. Upon sensing the movement the sensor transmits the data to the microcontroller which furthermore the Light to switch ON [4]. Similarly, as soon as the vehicle or an obstacle goes away the Light gets switched OFF as the sensor senses an object at the same time the status(ON/OFF) of the street light can be accessed from anywhere and anytime through the internet. This project is implemented with the smart embedded system which controls the street lights based on detection of vehicles or any other obstacles on the street.W he never the obstacle is detected on the street within the specified time the light will get automatically ON/OFF according to the obstacle detection and the same information can be accessed through the internet. The real-time information of the street light(ON/OFF Status) can be accessed from any time, anywhere through internet.

/pdf/internet-of-things-based-intelligent-street-lighting-system-4dr1960of4.pdf

Internet of things based intelligent street lighting system for smart city

The system is mainly used for smart and weather adaptive lighting in street lights. The project is implemented with smart embedded system that controls the street light based on detection of sunlight. During the night time the street light gets automatically ON and during the day time it gets automatically OFF. The ON/OFF can be accessed anywhere anytime through internet. A camera is placed on top of the street light to track the actions performed on the road where the footages are stored in a server. In addition to this, a panic button is placed on the pole, in-case of any emergency or danger, the person in danger can press this button which raises an alarm at the nearby police station. Whenever the panic button is pressed, the footage at that time recorded by the camera is sent directly to the cloud account. The access of the account is given to the particular police station by which they can view the incident's spot. Each area's street lights are connected to the particular area's police station and each of them has a cloud accessible account. The manual operation using GSM technology is completely eliminated. Thus the system is mainly designed to ensure safety and to prevent energy wastage.

Iot based smart and adaptive lighting in street lights

A highly populated country like Bangladesh faces too much traffic jam. Sometimes emergency vehicles like ambulance, fire-fighter get stuck in the traffic causing threat to life in many cases. It is important to give priority to this car and help to clear its path. But it is difficult or sometimes impossible for traffic police to handle this. For this reason, we need an automated system that will be able to detect an emergency car in heavy traffic road, let the controller know or automatically navigate other cars to clear its path. In this work, we have proposed an automated system to detect emergency cars from CCTV footage using the deep convolutional neural network. Our method has shown good result in detecting and classifying emergency cars.

Emergency Vehicle Detection on Heavy Traffic Road from CCTV Footage Using Deep Convolutional Neural Network

Background/Objectives: This paper focus on the necessity of intelligent traffic system and the peculiar way of implementation with embedded system tools. Here it is implemented using an object counting methods and detection of emergency vehicles simultaneously thereby control the traffic signals based on the priority outcome. Methods/Statistical analysis: Presently various system do provide a cost effective solution, but the rate of successful operation is bad. Inductive loop detectors installed under surface, this fails in case of poor road condition and so. In the other system, the density is found by installing IR detectors along the side of the lane. These systems operate less efficiently where they are not applicable in the real time process. This method uses image acquisition method using a real time live video stream and the algorithm is processed using MATLAB. Results/Findings: The results obtained with the prototype are much encouraging and the system does help the present traffic control system to be more efficient. Conclusion/Application: Computer Vision being one of the most researched are for the future technologies, this system will add gain to this sector with efficient operation replacing the current primitive timer traffic control system. This helps the emergency casualties to be attended quickly without panic of traffic congestion.

Smart Control of Traffic Signal System using Image Processing

Background/Objectives: This paper focus on the necessity of automated street light system and the peculiar way of implementation with embedded system tools. As automation booming in the industry with a fast pace, the requirement of replacing the primitive operation of street lights with quite intelligence is necessary. Methods/Statistical Analysis: The previous systems were implemented with LDR and IR sensors, here the presence of movement in the roads are sensed by IR sensors and LDR powers the street lights only after evening. The excess use of IR sensors and energy involved in the above operation are reduced in our prototype. Here we use piezo electric sensors to detect the movement in the roads instead of IR sensors. The microcontroller MSP430 as the brain to control the processes involved 1 . Results/Findings: The results are found to be very encouraging and the sample results are presented in the results section of the paper. Conclusion/ Application: LEDs are going to be vital lighting option in near future due to its peculiar low power consumption and cost effective nature. Our prototype will help in eliminating the current sodium vapour street lamps with better LED comprised lamps operated smartly using LDR, and piezo knock sensor.

An Innovation in the Field of Street Lighting System with Cost and Energy Efficiency

Background/Objectives: To ensure pedestrian safety in highways predominantly at night. Application: By introducing piezoelectric sensors embedded on highways, which automates the notification lamps that help both pedestrian and drivers to know each other’s presence. Methods/Statistical Analysis: The basic method we implement is getting the feed of digital HIGH and digital LOW from the piezoelectric crystals. The state of the pedestrian cross decides the output signal of the notification lamp. This helps the fast drivers on the highway to adjust their acceleration with prior alert of movement on the road. The prototype result with few minutes delay of glowing, the notification lamp can be set in real time with little more depending on the length of the cross. Findings: The night time travelers on the highway have the difficulty of vision due to optical problems of the front vehicle glass. The irritation due to high beam of the opposite vehicles distract the proper vision of the road. The pedestrians from local area are becoming a casualty of this situation. And the speed at which the drivers come is not possible to reduce in small period of time. Prior alert is required for this.

A Smart/Efficient Method to Facilitate Highway Pedestrian Protection

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Smart Control of Traffic Signal System using Image Processing

An Innovation in the Field of Street Lighting System with Cost and Energy Efficiency

A Smart/Efficient Method to Facilitate Highway Pedestrian Protection