Vacant Spaces Research Articles

Household Solid Waste Management and Environmental Impacts in the Ibadan Metropolis, Nigeria

Given the current rate of urbanization, municipalities in most Nigerian cities have struggled with the collection, transportation, and disposal of solid waste. This is due to waste generation, both residential and commercial, occurring in a dispersed manner across homes, buildings, streets, parks, and even vacant spaces within communities. This manuscript aims to evaluate the state of municipal solid waste management in Ibadan, household solid waste storage practices, and the locations of solid waste storage containers (skip points) in relation to accessibility and health risks to the community, in accordance with Nigerian National Solid Waste Management Standards and other pertinent international standards. A structured questionnaire was distributed to 21 micro and small firms and 250 homes in each of the three local government areas of the metropolis, with descriptive statistics used to interpret the data. According to the study results, inadequate Municipal Solid Waste Management (MSWM) service delivery in the Ibadan metropolitan area can be attributed to several issues, including a lack of institutional coordination among urban planners. The study’s conclusions indicate that the state of MSWM in the sampled areas is either inadequate or has poor spatial coverage and container utilization. Lastly, the study primarily suggests that these measures can reduce problems associated with MSWM by encouraging public-private partnerships, fostering effective institutional coordination with urban planner consultants in MSWM and skip-point location, and motivating the community to adopt integrated sustainable Solid Waste Management (SWM) strategies.

A blockchain-enabled private parking space allocation with improved parking space utilization

With the rapid development of the world’s infrastructure, we are moving towards making cities smart, known as smart cities. To make smart cities sustainable, designing efficient solutions is needed to reduce traffic congestion due to the lack of parking spaces within the constrained land areas of many metropolitan city centres. Parking problems in urban areas can be reduced by sharing vacant private parking spaces with others. In this work, we propose a decentralized and shared private parking management system using blockchain, which helps private parking owners and users fulfil their demands without the involvement of central authority. The proposed parking allocation method assigns parking to a single user from multiple parking providers, but the requester does not need to relocate between different parking spaces. The proposed method significantly improves private parking space utilization compared to a state-of-the-art parking allocation system. Hence, the system satisfies more user requests and generates more profit for parking owners than the state-of-the-art parking allocation system. The proposed system is a winning strategy because it maximizes the utilization of private parking spaces for the entire community’s benefit and helps to reduce traffic congestion. Experiments conducted in the simulated environment validate the benefits of the proposed model and show that it outperforms the state-of-the-art parking allocation system. A prototype of the proposed system is also developed in the Ethereum blockchain to validate the work, and the gas cost used to deploy the proposed model is analyzed.

Lidar, Space, and Time in Archaeology: Promises and Challenges

Airborne lidar (light detection and ranging), which produces three-dimensional models of ground surfaces under the forest canopy, has become an important tool in archaeological research. On a microscale, lidar can lead to a new understanding of building shapes and orientations that were not recognized previously. On a medium scale, it can provide comprehensive views of settlements, cities, and polities and their relationships to the topography. It also facilitates studies of diverse land use practices, such as agricultural fields, roads, and canals. On a macroscale, lidar provides a means to comprehend broad spatial patterns beyond individual sites, including the implications of vacant spaces. A significant challenge for archaeologists is the integration of historical and temporal information in order to contextualize lidar data in the framework of landscape archaeology. In addition, a rapid increase in lidar data presents ethical issues, including the question of data ownership.

Demonstrating a Quartz Crystal Microbalance with Dissipation (QCMD) to Enhance the Monitoring and Mechanistic Understanding of Iron Carbonate Crystalline Films.

This paper reports the real time monitoring of siderite deposition, on both Au- and Fe-coated surfaces, using the changes in frequency and dissipation of quartz crystal microbalance with dissipation (QCMD). In an iron chloride solution saturated with carbon dioxide, buffered with sodium bicarbonate to pH 6.8, roughly spherical particles of siderite formed within 15 min, which subsequently deposited on the QCMD crystal surface. Imaging of the surface showed a layer formed from particles ca. < 0.5 μm in diameter. Larger particles are clearly deposited on top of the lower layer; these larger particles are >1 μm in diameter. Monitoring of the frequency clearly differentiates the formation of the lower layer from the larger crystals deposited on top at later times. The elastic moduli calculated from QCMD data showed a progressive dissipation increase; the modeling of the solid-liquid interface using a flat approximation resulted in a poor estimation of elastic and storage moduli. Rather, the impedance modeled as a viscoelastic layer in contact with a semi-infinite liquid, where a random bumpy surface with a Gaussian correlator is used, is much more accurate in determining the elastic and storage moduli as losses from the uneven interface are considered. A further step considers that the film is in fact a composite consisting of hard spherical particles of siderite with water in the vacant spaces. This is treated by considering the individual contributions of the phases to the losses measured, thereby further improving the accuracy of the description of the film and the QCMD data. Collectively, this work presents a new framework for the use of QCMD, paired with traditional approaches, to enhance the understanding of crystal deposition and film formation as well as quantify the often evolving mechanical properties.

Dynamic Spatio-Temporal Adaptive Graph Convolutional Recurrent Networks for Vacant Parking Space Prediction

The prediction of vacant parking spaces (VPSs) can reduce the time drivers spend searching for parking, thus alleviating traffic congestion. However, previous studies have mostly focused on modeling the temporal features of VPSs using historical data, neglecting the complex and extensive spatial characteristics of different parking lots within the transportation network. This is mainly due to the lack of direct physical connections between parking lots, making it challenging to quantify the spatio-temporal features among them. To address this issue, we propose a dynamic spatio-temporal adaptive graph convolutional recursive network (DSTAGCRN) for VPS prediction. Specifically, DSTAGCRN divides VPS data into seasonal and periodic trend components and combines daily and weekly information with node embeddings using the dynamic parameter-learning module (DPLM) to generate dynamic graphs. Then, by integrating gated recurrent units (GRUs) with the parameter-learning graph convolutional recursive module (PLGCRM) of DPLM, we infer the spatio-temporal dependencies for each time step. Furthermore, we introduce a multihead attention mechanism to effectively capture and fuse the spatio-temporal dependencies and dynamic changes in the VPS data, thereby enhancing the prediction performance. Finally, we evaluate the proposed DSTAGCRN on three real parking datasets. Extensive experiments and analyses demonstrate that the DSTAGCRN model proposed in this study not only improves the prediction accuracy but can also better extract the dynamic spatio-temporal characteristics of available parking space data in multiple parking lots.

Experimentation, privilege, and difference: The politics of do‐it‐yourself urbanism

AbstractThe Canterbury Earthquake Sequence of 2010–2012 was devastating for Christchurch, New Zealand, a city built on a floodplain. The sequence resulted in widespread damage across the central business district (CBD) and residential areas. Alongside, and in contrast to, orthodox planning responses by the New Zealand Government, playful, creative, and temporary projects emerged in vacant spaces. These were designed to bring back life and energy to the city centre, and such types of activity are referred to by scholars as do‐it‐yourself (DIY) urbanism. A primary critique of DIY urbanism in the literature relates to how it has the potential to contribute to gentrification, despite its amateurish appearance and mildly subversive politics. In Christchurch, a venue built from pallets—known as the Pallet Pavilion—was constructed by an organisation known as “Gap Filler” with the help of volunteers. Gap Filler emerged after the first earthquake, inserting creative projects to bring back life and energy to the damaged CBD. By examining the Pallet Pavilion, we show that, despite its potentially gentrifying effects, DIY urbanism interventions may open up a more inclusive politics of the city. Also, and paradoxically, in the case of the Pallet Pavilion, the exercise of privilege made this inclusive politics possible.

Deep learning and saliency-based parking IoT classification under different weather conditions

The world’s population is growing at an exponential rate, which has created a slew of new issues in our daily lives. Among these challenges is the difficulty of finding available parking spaces. To overcome this obstacle, an effective system for detecting vacant parking spaces is crucial, particularly in densely populated areas. Even though there are numerous parking detecting systems on the market today, they all have their own set of restrictions. There are primarily two types of parking systems available. The first is a hardware-based system that uses hardware to detect whether a space is vacant or occupied, and the second is a smart parking system that uses cameras to classify parking status. Vision-based parking systems are becoming increasingly popular due to benefits such as flexibility and cost efficiency. However, due to challenging weather conditions and various occlusions caused by objects, such systems are challenging to develop. The limitations of a vision-based parking system must be addressed for it to become more accurate. To date, many researchers have attempted to incorporate deep learning-based parking systems with various algorithms but none of them has focused on reducing the complexity of Convolutional Neural Network (CNN) training through unsupervised pre-processing steps. In this study, an attempt is made to reduce the complexity of CNN by integrating salient features as a pre-processing step for normalizing weather conditions. It has been observed that salient features-based pre-processing makes the system more robust in terms of accuracy and time efficiency.

A Novel Rotor Harmonic Winding Configuration for the Brushless Wound Rotor Synchronous Machine

In the last decade, permanent magnet (PM)-free or hybrid PM machines have been extensively researched to find an alternative for high cost rare-earth PM machines. Brushless wound rotor synchronous machines (BL-WRSMs) are one of the alternatives to these PM machines. BL-WRSMs have a lower torque density compared to PM machines. In this paper, a new topology is introduced to improve the torque producing capability of the existing BL-WRSM by utilizing the vacant spaces in the rotor slots. The new topology has two harmonic windings placed on the rotor which induce separate currents. A capacitor is used between the two harmonic windings to bring the currents in phase with each other. The harmonic winding currents are fed to the rectifier which is also placed on the rotor. Due to additional harmonic winding, the overall field current fed to the rotor field winding has been increased and hence the average torque has also increased. Finite element analysis (FEA)-based simulations are performed using ANSYS Maxwell to validate the proposed topology. The results show that the average torque of the machine has been significantly increased compared to the reference model. The detailed comparison results are provided in this paper.

Fixing new municipalism discretely and discreetly. Power, participation, and the possibilities of progressive regimes

ABSTRACT The article examines the difficulty of progressive urban regimes to implement concrete and substantial policies. Looking at the reuse of three vacant public spaces in the city of Padova (Italy), it questions how the issues of capacity to act and citizen participation affect the promotion of a new-municipalist agenda. We show that: first, progressive urbanism is very unlikely to happen without an incumbency providing the capacity to implement radical objectives; and second, despite changes in discourse, already existing practices persist and coexist with new, progressive ones through institutional fixes. The case of Padova provides evidence of two “participation fixes” through which its new-municipalist government compensated for, although not resolving, the lack of coalitional and relational governing resources: a discrete implementation of the outcomes of participatory processes and; a discreet use of participatory processes as means to avoid conflict.

Co-doping strategies for advanced solid state electrolytes with lithium salt: a study on the structural and electrochemical properties of LATP

The commercialization of lithium-ion batteries has revolutionized the field of energy storage, yet their usage of organic electrolytes has led to significant safety concerns. Solid-state electrolytes have emerged as a promising solution to these issues, enabling the development of high-performance solid-state lithium batteries. The NASICON-type solid electrolyte Li1.3Al0.3Ti1.7P3O12 (LATP) has demonstrated excellent properties and significant potential. This study involves the solid-state synthesis of LATP electrolytes doped with Cobalt and Silicon. Furthermore, adding 8% LiBr into LATP-0.04 significantly enhanced ionic conductivity, reaching a value of 3.50 × 10−4 S cm−1. This can be linked to lithium salt filling vacant spaces between grains, resulting in a significant drop in grain boundary resistances. The electrochemical analysis through Linear Sweep Voltammetry (LSV) indicates that the investigated material demonstrates the capability to sustain stability and functionality even under the influence of elevated voltages, notably up to 5.45 V. These findings imply that optimal cobalt doping and Lithium salt contribute to superior ionic conductivity compared to pristine LATP.

Active Darcy's Law.

While bacterial swarms can exhibit active turbulence in vacant spaces, they naturally inhabit crowded environments. We numerically show that driving disorderly active fluids through porous media enhances Darcy's law. While purely active flows average to zero flux, hybrid active/driven flows display greater drift than purely pressure-driven flows. This enhancement is nonmonotonic with activity, leading to an optimal activity to maximize flow rate. We incorporate the active contribution into an active Darcy's law, which may serve to help understand anomalous transport of swarming in porous media.

Smart Car Parking System Using Raspberry Pi

This paper deals with a simple smart vehicles parking system by using basic components like micro controller, IR Sensors, Servo Motor, LCD etc. Parking, offered in malls, shopping areas, etc., are provided with help of a person which is very time consuming. Because of this, we created a straightforward vehicle parking system that uses IR sensors installed at parking spaces to detect the presence of parked vehicles, an LCD display board that shows the number of vacant and occupied parking spaces, and an LCD display board that shows the number of parking spaces currently available. Therefore, the research methodology work solution creates and implements an experimental setup that will regulate traffic in parking areas while also informing drivers about free spots. The main function of the servomotor is to permit and prohibited vehicles in and out of indoor spaces by opening and turning off the entry or exit barrier according to the data obtained from the IR sensors which are present on the entry gate, exit gate, parking spots.

Adaptive Reuse of High-Rise Buildings for Housing: A Study of Istanbul Central Business District

The abrupt shift to remote work due to the Covid-19 pandemic increased vacant office spaces globally, especially in high-rent central business districts (CBDs). These vacant office spaces offer the potential for conversion into housing, addressing the shortage of affordable housing in central areas. Additionally, this topic presents a unique experimental ground for architecture students. This study focuses on the Istanbul CBD as a case study, examining the historical developments that led to a rise in office vacancy rates and housing inequality, and exploring the potential for adaptive reuse of these vacant office buildings. A key focus of this study is to underline the pedagogical value of adaptive reuse, highlighting how such projects can inspire more diverse and equitable housing models, fostering experimental and sustainable design approaches. It systematically evaluates the outcomes of a 4th-year architectural design studio that focuses on the adaptive reuse of the Tat Towers in the Istanbul CBD, a structurally vacant high-rise office building, and asks: How does the context of adaptive reuse enable a different design approach, and, potentially, new spatial norms and standards to emerge, and how might this hold a pedagogical value for architecture education? Following these questions, the article discusses how norms and standards are not only culturally but also typologically contextual, and how the students have explored how norms and standards might change, outlining new design approaches to adaptive reuse.

Smart Parking Slot Management System Using IOT

The paper proposes an innovative approach to tackle the pressing issue of efficient parking space management amidst the backdrop of rapid urbanization and escalating vehicle ownership rates. Through the amalgamation of Internet of Things (IoT) technology and ultrasonic sensors, the Smart Parking Slot Management System (SPSMS) emerges as a promising solution. Within this system, IoT-enabled devices, particularly ultrasonic sensors, are strategically deployed within parking slots to constantly monitor their occupancy status in real-time. These sensors function by detecting the presence or absence of vehicles through precise measurements of the distance between the sensor and the ground surface. Subsequently, the collected data is seamlessly transmitted wirelessly to a centralized server or cloud-based platform via internet connectivity. Upon reception of sensor data, the central server undertakes robust processing and analysis to ascertain the availability of parking slots within the designated area. End-users can conveniently access this pertinent information through a dedicated mobile application or a web interface, facilitating effortless identification and reservation of vacant parking spaces. The system further enhances user experience by incorporating automated notifications, alerting users to nearby available parking slots, alongside real-time updates on parking availability and robust reservation management functionalities. Keywords: Internet of Things, Thing Speak, Arduino Uno, ultrasonic sensor, Node MCU.

Spatial arrangement and density variations in the cell envelope of Deinococcus radiodurans.

The cell envelope of the poly-extremophile bacterium Deinococcus radiodurans is renowned for its highly organized structure and unique functional characteristics. In this bacterium, a precise regularity characterizes not just the S-layer, but it also extends to the underlying cell envelope layers, resulting in a dense and tightly arranged configuration. This regularity is attributed to a minimum of three protein complexes located at the outer membrane level. Together, they constitute a recurring structural unit that extends across the cell envelope, effectively tiling the entirety of the cell body. Nevertheless, a comprehensive grasp of the vacant spaces within each layer and their functional roles remains limited. In this study, we delve into these aspects by integrating the state of the art with structural calculations. This approach provides crucial evidence supporting an evolutive pressure intricately linked to surface phenomena depending on the environmental conditions.

Determination of land surface temperature and urban heat island effects with remote sensing capabilities: the case of Kayseri, Türkiye

Kayseri, a densely urbanized province in Türkiye, grapples with pressing challenges of air pollution and limited green spaces, accentuating the need for strategic urban planning. This study, utilizing Landsat 8 and Landsat 9 satellite imagery, investigates the evolution of land surface temperatures (LST) and urban heat island (UHI) effects in key districts—Kocasinan, Melikgazi, Talas, and Hacılar—between 2013 and 2022. This research has been complemented with an analysis of the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Built-Up Index (NDBI), exploring correlations among the LST, UHI, NDVI, and NDBI changes. The findings indicate that a significant portion (65% and 88%) of the study area remained unchanged with respect to the NDVI and NDBI differences. This research’s findings reveal that a substantial portion (65% and 88%) of the study area exhibited consistency in the NDVI and NDBI. Noteworthy increases in the NDVI were observed in 20% of the region, while only 4% exhibited higher NDBI. Strikingly, the UHI displayed strong negative correlations with the NDVI and robust positive correlations with the NDBI. The LST changes demonstrated a reduced temperature range, from 21 to 51 °C in 2013, to 18 to 40 °C in 2022. Localized environmental factors, notably at the National Garden site, showcased the most significant temperature variations. Notably, the UHI exhibited strong negative correlations with the NDVI and strong positive correlations with the NDBI. The study’s results emphasize the interplay among the NDBI, LST, and UHI and an inverse relationship with the NDVI and NDBI, LST, and UHI. These findings hold implications for urban planning and policymaking, particularly in the context of resilient and sustainable land use planning and the UHI mitigation. This research underscores the intricate interplay among the NDBI, LST, and UHI, highlighting an inverse relationship with the NDVI. These findings hold crucial implications for resilient and sustainable urban planning, particularly in mitigating the UHI effects. Despite limited vacant spaces in Kayseri, geospatial techniques for identifying potential green spaces can facilitate swift UHI mitigation measures. Acknowledging Kayseri’s complex dynamics, future research should delve into the UHI responses to urban morphology and design, extending this methodology to analyze the UHI effects in other Turkish cities. This research contributes to a broader understanding of UHI dynamics and sustainable urban planning practices, offering valuable insights for policymakers, urban planners, and researchers alike.

Prospects and Sustainability in Car Parking Systems in select Neighbourhoods of Port Harcourt Municipality

Well-organised parking in cities promotes urban environmental sustainability and livability. The study aimed to explore and sustain the prospects of parking systems in neighbourhoods of Port Harcourt Municipality, Nigeria. The objectives were ascertaining the parking systems of neighbourhoods of the study area, identifying prospects of parking systems of neighbourhoods of the study area, and identifying measures to sustain the prospects of parking systems in neighbourhoods of the study area. The study adopted a quantitative approach using a descriptive research design. The study employed stratified and simple random sampling techniques to select sampled neighbourhoods and respondents for the study. A stratified sampling technique was employed to group the neighbourhoods into 3 strata (high, medium and low densities). 3 neighbourhoods were selected to represent each stratum namely: PH Township (high density), Orominike-D/Line (medium density) and Orije Layout- Old GRA (low density) for the study. A total of 397 respondents were determined and interviewed using the Taro Yamane formula at a 5% precision level. The study revealed that there exist on-street and off-street parking systems with various parking types including parallel, perpendicular, echelon angled and double-parking types. These parking systems are both off-street and on-street types. The prospects of the parking systems parking spaces in the building premises, along the carriageway on the street, in front of the building, space in other premises, public places and open spaces within the neighbourhoods. These conditions have promoted orderliness, safety, and security of road users such as residents, businesses, and visitors. The study found measures to sustain the prospects are creating more parking spaces/lots and designate parking area in the neighbourhoods, building a paid-parking facility in the neighbourhoods, marking parking areas clearly, government should enforce provision of parking spaces on premises, avoiding parking in the front of buildings where the space is inadequate, stop using designated parking spaces for other purposes, parkers to stop double parking in the streets, and impound broken-down vehicles in the streets. Therefore, to further sustain and enhance the prospects of parking systems in the neighbourhoods, the study recommended all government agencies should synergise to prepare parking plans for neighbourhoods. identify vacant spaces at strategic locations in the neighbourhoods where off-street parking facilities will be provided, clearly mark out designated parking spaces and parking lots along the streets, introduce a paid-parking system in the neighbourhoods, introduce one-side (parallel or perpendicular) parking along streets that are narrow in width, regulate and enforce the elimination of street trading, indiscriminate parking, removal of bad vehicles and discourage double parking in the neighbourhoods.

Short-term prediction of on-street parking occupancy using multivariate variable based on deep learning

Short-term prediction of on-street parking occupancy is essential to the ITS system, which can guide drivers in finding vacant parking spaces. And the spatial dependencies and exogenous dependencies need to be considered simultaneously, which makes short-term prediction of on-street parking occupancy challenging. Therefore, this paper proposes a deep learning model for predicting block-level parking occupancy. First, the importance of multiple points of interest (POI) in different buffers is sorted by Boruta, used for feature selection. The results show that different types of POI data should consider different buffer radii. Then based on the real on-street parking data, long short-term memory (LSTM) that can address the time dependencies is applied to predict the parking occupancy. The results demonstrate that LSTM considering POI data after Boruta selection (LSTM (+BORUTA)) outperforms other baseline methods, including LSTM, with an average testing MAPE of 11.78%. The selection process of POI data helps LSTM reduce training time and slightly improve the prediction performance, which indicates that complex correlations among the same type of POI data in different buffer zones will also affect the prediction accuracy of LSTM. When there are more restaurants on both sides of the street, the prediction performance of LSTM (+BORUTA) is significantly better than that of LSTM.

Advancing rainwater treatment technologies for irrigation of urban agriculture: A pathway toward innovation

Urban agriculture (UA) has emerged for local food security since the 1960s. However, the access to sufficient and safe irrigation water remains a significant constraint. Municipal water supply, though commonly used in UA practices, proves unsustainable due to high costs, intensive energy consumption, and limited availability in many vacant urban spaces. In contrast, rainwater harvesting (RWH) exhibits a potential as a non-traditional water supply for urban farming. This article aims to provide insights into the advantages and challenges associated with RWH for UA irrigation, analyze existing low-cost RWH treatment technologies, and identify a visionary way toward innovative, new-generation RWH treatment processes in UA practices. Despite a promising water source, harvested rainwater is challenged for crop irrigation owing to the presence of various contaminants (e.g., waterborne pathogens, potentially toxic metals and metalloids, and synthetic organic chemicals). While established RWH treatment processes (e.g., first flush diversion, sedimentation, solar disinfection, chlorination, UV irradiation, granular filtration, and bio-sand filtration) can remove certain pollutants, they cannot offer viable treatment solutions for UA irrigation due to different technical, economic, and social restrictions. Particularly, their capacity to reliably remove contaminants of emerging concern in runoff remains limited or uncertain. Consequently, it is essential to develop next-generation RWH treatment technologies tailored specifically for UA irrigation. To this end, three fundamental principles are recommended. First, the focus should be on technically viable, low-cost, simple-operation, and easy-maintenance treatment technologies capable of simultaneously addressing traditional and emerging runoff contaminants, while minimizing the production of undesirable treatment byproducts. Second, advancing the understanding of the water, soil, and crop interactions enables the development of “right” RWH treatment processes for irrigation of “right” crops at a “right” place. Last, crop nutrients, if possible, are retained in rainwater to reduce the nutrient demand for crop production. The insights and perspectives have far-reaching implications for water conservation, stormwater management, and the integration of water, food, and energy systems within the urban environment.

Integrating YOLOv8 with Fuzzy Logic System: A Novel Hybrid Approach for Efficient Parking Slot Availability Management

In urban areas, the challenge of finding parking spaces has become a significant concern, leading to congestion, wasted time, and increased pollution. Traditional parking management systems often lack the efficiency needed to address this issue adequately. In this paper, a novel approach was proposed to smart parking management that integrates the YOLOv8 model and fuzzy logic system. YOLOv8, a state-of-the-art object detection algorithm, enables real-time detection and tracking of vehicles within parking lots. By utilizing YOLOv8, the system can accurately identify vacant parking spaces in a timely manner. Furthermore, fuzzy logic was employed to enhance decision-making in selecting the optimal parking slot for users. Fuzzy logic enables the system to consider various factors such as proximity to the destination, parking space size, and distance from the entrance. By incorporating fuzzy logic into the decision-making process, the system can provide personalized recommendations tailored to individual user preferences and parking requirements. Based on the fuzzy inputs namely distance from entrance, proximity to exit and space, the system analyzes the best parking slot and assigns “rank” which is also fuzzy output. The decision can be made based on the rank provided to every slot of the parking lot. Slots with the highest rank should be preferred for parking because they are more suitable as they provide ease to parking the cars and can be suitable to customized needs of the users. The model can be deployed with LCD screens at various parking lots in order to save fuel and time of the commuters.