ETMS: Efficient Traffic Management System for Congestion Detection and Alert using HAAR Cascade

Rapid social development has resulted in the emergence of a new major societal issue: urban traffic congestion, which many cities must address. In addition to making  it more difficult for people to get around town, traffic jams are a major source of the city's pollution crisis. In order to address the problems of automobile exhaust pollution and congestion, this paper uses the system dynamics approach to develop a model to study the urban traffic congestion system from the perspectives of trucks,private cars, bikes and public transportation. This project proposes a system for detecting vehicles and sending alerts when traffic levels rise to dangerous levels using Haar Cascade and Fuzzy Cognitive Maps (FCP). The proposed system uses Haar Cascade to detect moving vehicles, which are then classified using FCP. The system can make decisions based on partial or ambiguous information by utilising FCP, a soft computing technique, which allows it to learn from past actions. An algorithm for estimating traffic density is also used by the system to pinpoint active areas. In congested areas, the system will alert the driver if it anticipates a collision with another vehicle and also Experiments show that the proposed system is able to accurately detect vehicles and provide timely alerts to the driver, drastically lowering the probability of accidents occurring in heavily travelled areas. The importance of introducing such a system cannot be overstated in today's transportation system. It's a big deal for the future of intelligent urban planning and traffic control. Congestion relief, cleaner air, and increased security are just some of the long-term benefits that justify the high initial investment. To add, this system is adaptable to suburban and rural areas, which can also experience traffic congestion issues

Examining trade-offs between social, psychological, and energy potential of urban form

Urban planners are often challenged with the task of developing design solutions which must meet multiple, and often contradictory, criteria. In this paper, we investigated the trade-offs between social, psychological, and energy potential of the fundamental elements of urban form: the street network and the building massing. Since formal methods to evaluate urban form from the psychological and social point of view are not readily available, we developed a methodological framework to quantify these criteria as the first contribution in this paper. To evaluate the psychological potential, we conducted a three-tiered empirical study starting from real world environments and then abstracting them to virtual environments. In each context, the implicit (physiological) response and explicit (subjective) response of pedestrians were measured. To quantify the social potential, we developed a street network centrality-based measure of social accessibility. For the energy potential, we created an energy model to analyze the impact of pure geometric form on the energy demand of the building stock. The second contribution of this work is a method to identify distinct clusters of urban form and, for each, explore the trade-offs between the select design criteria. We applied this method to two case studies identifying nine types of urban form and their respective potential trade-offs, which are directly applicable for the assessment of strategic decisions regarding urban form during the early planning stages

Towards explaining the positive effect of vegetation on the perception of environmental noise

Audio-visual interactions play a significant role when humans perceive the environment. In this review paper, it is analysed how visible vegetation can be used to mitigate negative environmental noise perception with a focus on noise annoyance. Existing research has been analysed in view of three potentially explaining mechanisms namely source (in) visibility, the mere presence of visible green, and vegetation as a source of natural sounds. The source concealing potential vegetation has cannot fully explain reported findings. The restorative properties of visible vegetation seems the dominant mechanism. Visible natural features of good quality lead to sustained attention restoration and stress relief, counteracting negative outcomes of endured environmental noise exposure. There is strong evidence that noise annoyance experienced at home largely decreases when outdoor nature is present in the window pane. Additional support regarding the importance of such micro-restorative experiences is found by research at the working place, in hospital environments and at schools. Non-directly visible neighbourhood green shows to be positive as well, but with a smaller impact on noise perception. Natural sounds and especially bird songs are relaxing on theirselves, and support the restorative action of nature by suggesting nearby and vital nature. Based on rough quantitative estimates, the equivalent level reduction of (high quality) visible green from home could reach 10 dBA. This equivalent level reduction comes on top of the physical sound pressure level reduction one might obtain behind vegetation belts. At higher exposure levels, the improved noise perception one can get from vegetation is larger than at lower levels. The bulk of literature is concerned with road traffic noise, although scarce research suggests the applicability is much broader. Personal characteristics are expected to play a role in the interaction between noise perception and vegetation too

Learning middle school mathematics through student designed and constructed video games

Mathematics achievement is an area in which American precollege students are faltering. Emerging research suggests that making mathematics instruction relevant and applicable in the lives of youth may impact math achievement, especially when it capitalizes on high-interest technologies such as video games. Employing a quasi-experimental and descriptive approach, this study examined the mathematics (i.e., numbers and operations, algebra, geometry, measurement, and probability) that middle school students employed during their design and construction of video games. First, it examined the mathematics content learned by 19 sixth and seventh graders during their analysis, synthesis, and programming of three video game projects over 7 months. Second, it measured the ability of the student programmers to laterally transfer mathematics content from the technology context of game production to the traditional context of paper-and-pencil tests. Third, it evaluated student attitudes toward mathematics prior to and following video game design and construction. The performance of student programmers was compared with that of a control group of nonprogrammers on measures of transfer and affect. Results indicated that middle grade students successfully identified the events defining game play (e.g., motion, collisions, and scoring) of three, simple video game models. They successfully represented video game events in both mathematical and programming forms by writing and coding (a) boundary conditions using inequalities, (b) coordinate locations and identification of coordinate convergence, (c) directional headings, (d) uniform linear motion, (e) variable changes, and (f) probability-based consequences. They were also successful in writing programming code for their own functional video games, with a high percentage of relevant mathematics content incorporated therein. However, while treatment students transferred mathematical knowledge from the technology to the traditional context, it appeared that, without explicit bridging, the transfer was no better than comparison students. Treatment students also demonstrated no significant changes in attitude associated with designing and constructing video games. This study demonstrated that video game design and construction can be a viable - although not significantly different - method, cognitively and affectively, of instructing age-appropriate, standards-based mathematics content

Gaining Insight into Determinants of Physical Activity using Bayesian Network Learning

Contains fulltext : 228326pre.pdf (preprint version ) (Open Access) Contains fulltext : 228326pub.pdf (publisher's version ) (Open Access)BNAIC/BeneLearn 202

QUALITY-OF-SERVICE PROVISIONING FOR SMART CITY APPLICATIONS USING SOFTWARE-DEFINED NETWORKING

In the current world, most cities have WiFi Access Points (AP) in every nook and corner. Hence upraising these cities to the status of a smart city is a more easily achievable task than before. Internet-of-Things (IoT) connections primarily use WiFi standards to form the veins of a smart city. Unfortunately, this vast potential of WiFi technology in the genesis of smart cities is somehow compromised due to its failure in meeting unique Quality-of-Service (QoS) demands of smart city applications. Out of the following QoS factors; transmission link bandwidth, packet transmission delay, jitter, and packet loss rate, not all applications call for the all of the factors at the same time. Since smart city is a pool of drastically unrelated services, this variable demand can actually be advantageous to optimize the network performance. This thesis work is an attempt to achieve one of those QoS demands, namely packet delivery latency. Three algorithms are developed to alleviate traffic load imbalance at APs so as to reduce packet forwarding delay. Software-Defined Networking (SDN) is making its way in the network world to be of great use and practicality. The algorithms make use of SDN features to control the connections to APs in order to achieve the delay requirements of smart city services. Real hardware devices are used to imitate a real-life scenario of citywide coverage consisting of WiFi devices and APs that are currently available in the market with neither of those having any additional requirements such as support for specific roaming protocol, running a software agent or sending probe packets. Extensive hardware experimentation proves the efficacy of the proposed algorithms