Database For Future Use Research Articles

Automating the Generation of NVD CVE Fixes using Generative AI and RAG

As modern software applications increase, the challenge of addressing security vulnerabilities [1] will increase. Generating fixes for these vulnerabilities rely on manual intervention—a process that can be both timeconsuming and difficult to scale. In this paper, we propose an automated approach to CVE fix generation, leveraging data from the National Vulnerability Database (NVD) [2], a local vector database for efficient storage, and Generative AI to produce relevant fixes based on vulnerability descriptions. Our approach involves first loading all publicly available CVE data into a vector database, indexed by CVE ID and metadata for efficient retrieval. When a query for a CVE fix is made, then using Generative AI using custom prompts to provide fixes based on the vulnerability descriptions stored in the database. The generated solutions are stored back in the database for future use, or for review. In the methodology section, we demonstrate how this system can automate the generation of effective CVE fixes in a matter of seconds, streamlining a traditionally manual and time-consuming process. With the findings suggest that the proposed system can reduce the manual/time consuming effort on the teams while enhancing the speed and accuracy of vulnerability remediation

AI Kitchen

Purpose: Using several smart gadgets makes the kitchen smart. The picture of the kitchen from ancient has drastically changed. Now, the kitchen is glorified using modern technology. The kitchen chimney, microwave oven, etc., is more convenient for the kitchen. Now, AI has come, and every day, more and more devices are becoming AI-enabled. In this scenario, we demonstrated the project in an AI-enabled kitchen. There are several advantages of AI-enabled kitchens over intelligent kitchens. AI will handle our most repetitive and monotonous work. Also, AI will take care and protect from any accident before it happens, which generally happens due to forgetfulness or carelessness. Design/Methodology/Approach: We installed a CPU inside the home. We installed an action controller in the kitchen that connects all kitchen gadgets. One PTZ camera is installed in such a place that captures the gas oven and the entire kitchen environment. Our camera is the point-to-zoom (PTZ) type, so it can rotate the lens and zoom to capture any incident for better understanding or to detect the perfect image for accurate detection. Our camera is running all the time, which means round the clock. It always captures the image and processes the image by CPU. If any event matches with the event database, it sends the command to the action controller to take the action. If a new event is detected, it will learn from it and save it into the database for future use. Findings/Result: The complete system is the conceptual-based research work. However, every part of the module or section is based on practical research work. So, once the system is deployed in the practical field, it will work without issues. In a typical kitchen, we must always pay attention, like the regulator is on if the milk is left for a long time in the gas oven. So, this kind of tension and anxiety will go for retired. All events will be taken care of by our AI-enabled system. Once the system is installed, it will run autonomously; there is no need to take care of or follow up. Once the system detects some issue, the system will notify the concerned person. Originality/Value/Novelty: Nowadays, intelligent gadgets are taking place in the home. Smart devices, especially in the kitchen, make life easy. Using AI, we can get more benefits and security for the kitchen. We studied several research works. Most of the researchers automated kitchen gadgets. But still, the problem exists. All gadgets should be under centralized control to get better safety and control. Through this research work, we described how to create safety and control in the kitchen environment. This research works to provide more value to the modern, smart kitchen. Type of Paper: Conceptual Research.

Study of Gamma-ray Shielding of Two Different Heavy Metals and their Combination for Cs-137 and Co-60 Sources

This article presents data collected by measurements of lead (Pb) and iron (Fe) and their combination as heavy shielding materials. Measurements were performed using gamma photon energies of 662, 1173, and 1332keV for the Cs-137 and Co-60 sources. The theoretical data part was calculated using WinXCom, Phy-X, and Py-MLUBF software packages. Tables and graphs of the photon Mass Attenuation Coefficient (MAC), Linear Attenuation Coefficient (LAC), Half Value Layer (HVL), Tenth Value Layer (TVL) and Mean Free Path (MFP) are presented for both heavy metals and their combination to study the shielding properties experimentally and theoretically. The results will contribute to the ongoing research as a database for future use.

Finding And Matching the Lost Victim Using AI and ML

Abstract: In today’s virtually and technologically evolving world, technology is being used for ease of human efforts and for faster results. Appropriate security upgrade and enhancements are required to be balanced so that the users can rely and trust their personal information on these technologies. Simultaneously, persons who goes missing if found also, there’s no way to identify if it’s the actual person or not. Also, many people don’t try to help in these matters concerning about their life safety from goons and mafias because many missing cases occurs from kidnapping and abduction etc. So, in this paper we are proposing and fabricating a project that will help to resolve such type of incidences. The project must require the public support but will ensure the public safety by keeping the identity constraints safe and sound. This project is going to rotate the tedious and complex phases of finding the missing person by mere man-force. This technology is going to help the Police Force, the Cyber Cell Authorities as well the parents/relative/guardian of the missing victim. The User Interface will be easy to use and adaptive, the features and functionality will be top-notch as it will be designed in PyQt5 GUI. The main process is of matching the lostfound victims photograph by using the K-NN Algorithm (AI & ML concepts). All the gathered data will be kept safe in the PostgreSQL’s Database for future use. The algorithm will convey through calculation of data from pictures that if the person is actually matching or not. In this way the fabricated project will execute. For further details and data, a web portal will be made for the local public about the latest and recent updates about the cases.

An Intelligent Healthcare Cyber Physical Framework for Encephalitis Diagnosis Based on Information Fusion and Soft-Computing Techniques.

Viral encephalitis is a contagious disease that causes life insecurity and is considered one of the major health concerns worldwide. It causes inflammation of the brain and, if left untreated, can have persistent effects on the central nervous system. Conspicuously, this paper proposes an intelligent cyber-physical healthcare framework based on the IoT–fog–cloud collaborative network, employing soft-computing technology and information fusion. The proposed framework uses IoT-based sensors, electronic medical records, and user devices for data acquisition. The fog layer, composed of numerous nodes, processes the most specific encephalitis symptom-related data to classify possible encephalitis cases in real time to issue an alarm when a significant health emergency occurs. Furthermore, the cloud layer involves a multi-step data processing scheme for in-depth data analysis. First, data obtained across multiple data generation sources are fused to obtain a more consistent, accurate, and reliable feature set. Data preprocessing and feature selection techniques are applied to the fused data for dimensionality reduction over the cloud computing platform. An adaptive neuro-fuzzy inference system is applied in the cloud to determine the risk of a disease and classify the results into one of four categories: no risk, probable risk, low risk, and acute risk. Moreover, the alerts are generated and sent to the stakeholders based on the risk factor. Finally, the computed results are stored in the cloud database for future use. For validation purposes, various experiments are performed using real-time datasets. The analysis results performed on the fog and cloud layers show higher performance than the existing models. Future research will focus on the resource allocation in the cloud layer while considering various security aspects to improve the utility of the proposed work.

Analysis of Text Data For Stock Prediction

Abstract: Accounting for price fluctuations and understanding people's emotions can help to improve stock price forecasting. Only a few models can decipher financial jargon and have stock price change datasets that have been labelled. In this project, we used text mining techniques to extract high-quality data from news and tweets published by legitimate businesses on the internet, allowing us to analyse, decide, and update our database for future use. In this paper, we propose an information gathering and processing framework that combines a natural language processing tool with our algorithms. We use natural language processing and machine learning techniques to make predictions. The result demonstrates the algorithm's ability to foresee favorable outcomes.

A case study on slope instability of Punatshangchhu Hydroelectric Project Authority-I Dam in Bhutan

The stability of the slope is a greater concern to engineers and geoscientists as the socioeconomic consequences of the failures are huge. One such case is the slope instability of right bank of Punatshangchhu Hydroelectric Project Authority (PHPA-I) dam, Bhutan. The main geology of dam site is characterized by coarse-grained quartzo-feldspathic and biotite- muscovite gneiss. Since the start of the project in 2008, project encountered several geotechnical problems. During excavation at dam pit area, the shear zone got day-lighted which triggered a huge movement of right bank of dam in 2013. As such, project authority has carried out various stabilization measures in arresting movement of right abutment of dam. In this paper, subsurface profile construction from boring log data using Rockwork software (Rocscience) for PHPA-I dam site is presented. The subsurface profile once constructed can be used for identifying the critical slip surface and can also be used in modeling for slope stability analysis. Moreover, it can be a database for future use in that part of the study area.

La constitución de una memoria terminológica: elaboración de terminologías bilingües en programas de memoria de traducción

Computer-aided translation systems (CAT) based on Translation Memories (TM) are a widely diffused technology that uses database and code-protection features to improve the quality, efficiency and consistency of the human translation process. These systems basically consist of a textual database in which each source sentence of a translation is stored together with the target sentence (this is called a translation memory “unit”). New and changed translation proposals will then be stored in the database for future use. This textual database – the kernel of the system – is combined with a terminological database (TDB), which is used by translators to store independently, terminological equivalences or translation units of particular value.In this paper the authors outline a first draft of a methodology that describes the preparation of a bilingual terminology from – and within – TM applications. The bilingual corpus produced is called the ‘terminological memory’ of the translator.

The challenge of a successful discrimination of ancient marbles (part II): A databank for the Alpine marbles

Numerical data on scientific analytical characteristics of the Alpine marbles are presented in this paper in order to provide a database for future use when investigating artefacts of that region. The Alpine marbles used already in Roman times can be subdivided into two major groups. Those of the first group, bound to the “Koralpe-Wölz-System”, are medium to coarsegrained white marbles usually of good to excellent quality. Well-known quarries of this group are e.g. Gummern or the Slovenian Pohorje/Bachern marbles. The degree of discrimination of these marbles from each other is very bad when only stable isotope analysis is applied. However, by using discrimination analysis and computing a large set of analytical variables a separation of the datafields of these quarries can be improved considerably.The marbles of the second group from the “Drauzug-Gurktal-System”, the “Pörtschach marbles”, are visually indistinguishable but they are significantly different in their petrological and chemical characteristics. Thus they can safely be assigned to their source.The data presented in the “Supplementary Material” are intended to supply a databank for further marble provenance analysis of artefacts to be checked against Alpine marbles. For the sake of comparability, the methods of analysis of a sample to be investigated have to be in strict compliance with the analytical methods that were used for the preparation of this databank.

A Review of Heavy Metals in Coastal Surface Sediments from the Red Sea: Health-Ecological Risk Assessments.

The heavy metal (HM) pollution in sediment is of serious concern, particularly in the Red Sea environment. This study aimed to review and compile data on the concentrations of four HMs (Cd, Cu, Pb, and Zn) in the coastal surface sediments from the Red Sea, mainly from Saudi Arabia, Egypt, and Yemen, published in the literature from 1992 to 2021. The coastal sediments included those from mangrove, estuaries, and intertidal ecosystems. It was found that the mean values of Cd, Cu, Pb, and Zn in coastal Red Sea sediments were elevated and localized in high human activity sites in comparison to the earth upper continental crust and to reference values for marine sediments. From the potential ecological risk index (PERI) aspect, 32 reports (47.1%) were categorized as ‘considerable ecological risk’ and 23 reports (33.8%) as ‘very high ecological risk’. From the human health risk assessment (HHRA) aspect, the non-carcinogenic risk (NCR) values (HI values < 1.0) of Cd, Cu, Pb, and Zn represented no NCR for the ingestion and the dermal contact routes for sediments from the Red Sea countries. The reassessment of the HM data cited in the literature allowed integrative and accurate comparisons of the PERI and HHRA data, which would be useful in the management and sustainable development of the Red Sea area, besides being a helpful database for future use. This warrants extensive and continuous monitoring studies to understand the current and the projected HM pollution situation and to propose possible protective and conservative measures in the future for the resource-rich Red Sea ecosystem.

Development of RFID based Automatic Warehouse Management System: A Case Study of ROK industries Limited Kenya

In the supply chain and logistics industry, the precision of the data assets inventory plays a crucial role in warehouse activities. The operations like storage locations arrangement, inventory management, and maintaining the flow of incoming and outcoming goods lead to the success of the warehouse. Nowadays, most people are preferring online shopping all over the world because it is faster than local trade. Thus, there's massive information in the supply chain and logistics sector to explore in order to improve operations of the warehouse such as receiving, ordering, shipping, storage assignment to facilitate the automation in the warehouse. This study is conducted to improve warehouse activities by automating storage and inventory management. A software program was developed with sets of rules, and an algorithm to optimize the inventory operations with the help of RFID technology. The predefined rules help in giving priorities to some of the selected products to store and retrieve in the indicated locations. The UHF RFID reader is attached to the entrance of the gate of the warehouse to facilitate the reading of incoming goods. Once the goods arrive in the warehouse, the storage location function will assign to each product the storage location and update status in the database. A handheld reader facilitates inventory management and communicates with the application via a wireless network and finally store data in the database for future use. After developing this system, a test was conducted for testing the feasibility and applicability of the system. The output showed that the inventory management operation was made strides, and the correctness of inventory location increased from 72.8% to 99%. The cycle time moreover decreases from 50 minutes to 18 minutes which is down to 28.79%.

The ADAMTS13 Family: In-Patient Trends and Outcomes of Thrombotic Thrombocytopenic Purpura

Introduction: Thrombotic thrombocytopenic purpura (TTP) is a rare, life-threatening disorder characterized by microangiopathic hemolytic anemia, thrombocytopenia, neurological symptoms, renal dysfunction and other end organ failure. It is associated with inherited or acquired antibody-mediated deficiency of ADAMTS13 resulting in an inability to cleave von Willebrand factor. It occurs in approximately 3 in 1 million adults and 1 in 10 million children annually. First line therapy is plasmapheresis, typically coupled with steroids. Patients recovering from TTP may demonstrate persistent or intermittent ADAMTS13 deficiency without symptoms or thrombocytopenia. Most relapses of acquired TTP occur in the first week after stopping plasma exchange. There are multiple factors contributing to relapses, which include age &amp;gt; 60, severe neurological symptoms at presentation and a persistently elevated lactate dehydrogenase. Thus young patients with low ADAMTS13 activity are appropriate candidates for prophylactic treatment. The early initiation of immune-modulatory therapy targeting the antibody inhibitor of ADAMTS13 could potentially reduce the number of plasma exchange procedures required to achieve remission, increase the response rate and decrease the incidence of relapses in patients with TTP. Since TTP is a rare disease, the aim of our study was to outline the trends and outcomes of hospitalizations due to TTP using the nationally representative database for future use in risk stratification and treatment protocols. Methods: We performed retrospective study using the National Inpatient Sample database, a part of the Healthcare Cost and Utilization Project (HCUP) of the agency for Healthcare Research and Quality (AHRQ). We extracted the study cohort of adult admissions with TTP from 2007-2017 by using International Classification of Diseases (9th/10th editions) Clinical Modification diagnosis codes. In the final study cohort we only included patients who received plasmapheresis to restrict patient population with active TTP disease. This approach has been validated in prior publications from administrative databases. Other diagnosis of interests and other comorbidities were identified by ICD-9/10-CM codes and Elixhauser comorbidity software. We utilized Cochran Armitage trend test and survey logistic multivariable regression modeling to analyze trends and predictors of outcomes with weighted analysis. Statistical analyses were performed using SAS software, version 9.4. Results: There were a total 22,054 hospitalizations due to TTP, which increased from 1,620 in 2007 to 1,870 in 2017. The median age was 47-years (IQR:33-60) with 25% hospitalizations among the age group of 18-34 years, 66.1% were females, 46.7% were Caucasians followed by 39.2% African American race. The overall length of stay was 16-days which declined from 17-days in 2007 to 15-days is 2017 (pTrend&amp;lt;0.001). In the study cohort, 14.5% were discharged to a facility, and 9.8% died during the hospitalization. In trend analysis, in-hospital mortality decreased (13.4% in 2007 to 8.02% in 2017; pTrend&amp;lt;0.001) but discharge to facilities increased (8.9% in 2007 to 14.4% in 2017; pTrend&amp;lt;0.001). Furthermore, in multivariable regression analysis, increasing age (OR 1.4; 95%CI 1.3-1.5; p&amp;lt;0.001), Caucasians (OR 1.4; 95%CI 1.2-1.7; p&amp;lt;0.001), pneumonia (OR 1.8; 95%CI 1.4-2.5; p&amp;lt;0.001), septicemia (OR 3.4; 95%CI 2.6-4.5; p&amp;lt;0.001), cardiovascular events (OR 2.2; 95%CI 1.5-3.2; p&amp;lt;0.0001), electrolytes imbalance (OR 1.4; 95%CI 1.1-1.9; p=0.005), and liver disorders (OR 1.7; 95%CI 1.1-2.6; p=0.02) were associated with higher odds of in-hospital mortality. Conclusion: In this study, we described national trends of hospitalizations and outcomes of TTP. We observed in-hospital mortality has decreased coupled with an increase in discharge to facilities over the past decade. We also identified risk factors for poorer outcomes, including advanced age, caucasian background and associated sepsis, revealing higher odds of in-hospital mortality. Early identifications of these potential risk stratifiers may play a crucial role in initiating early treatment in addition to identifying populations who may benefit from immune-modulatory therapy along with prophylactic plasma exchange. Disclosures No relevant conflicts of interest to declare.

Design and Implementation of a Web Based Health Information System

Health Information System aims at improving and enhancing the delivery of quality, data availability and administrative effectiveness of people’s health. Medical record has come under severe threat as a result of the manual system of medical record keeping in spite of its important functions. This system of record-keeping involves taking down patient data on pieces of paper, which are put into files and kept in cabinets. In fact, this is an improper means of documentation resulting in loss and mismatch of patient data, and time wastage. It is alsocumbersome, bulky and consumes a lot of the office space. In this paper, a complete web-based health information system is designed to solve these problems so as to enable users handle details on policies efficiently and effectively. A test of the system over various network topologies reveals that time taken to move a packet and received acknowledgment for standalone, LAN, WAN and Intranet is 3ms, 4ms, 8ms and 10ms respectively. These short periods of time show faster and efficient delivery of health activities. The Web Based HealthInformation System thus provides significant benefit to institutions as it can capture data and store it in the developed database for future use.&#x0D; Citation: Kwasi, T. M., Patrick, A.A, Amponsah Wellington, A. Design and Implementation of a Web-BasedHealth Information System, 2020; 5(3): 1－11.&#x0D; Received: August 4, 2019Accepted: September 30, 2020

Facilitating of knowledge transfer in a software development company

In an organization, knowledge transfer between its members is vital. Most studies conducted up to this date have focused on knowledge transfer in the field of industrial production. If in this branch of knowledge, where operations and processes have a certain degree of standardization and repeatability, this is done through initial and possibly periodic training, in the matter of software development things are more complicated. Tasks do not resemble with each other, most are unique and often require documentation before being resolved. Obtaining documentation from external environments often involves work on adapting to the organization’s requirements and to the project’s requirements also. In an organization without a constant direct interaction between the members, the transfer of knowledge requires much labor. In this paper, we propose the design and implementation of a software solution that will facilitate the transfer of knowledge between the developers of a software development company. This internal database will include the solutions identified, adapted, and used by programmers to solve non-familiar tasks. Also, a collection will be created with the errors encountered throughout the development and implementation process and their resolution, useful for all members of the organization. Every time a team will meet an unfamiliar functionality in an assigned task, it will consult the internal database. In this way, the solution will be easier reached and adapted from the source. External sources of documentation and research will only be used if the internal search has not returned a solution to the problem. In this case, following the solving steps, the familiar solution will be added to the internal database for future use. Finally, we will measure the benefits of the proposed and implemented solution. Ultimately, the rate of use of a solution stored in the database over a period of time will be measured, along with the average time of solving a task in the development process, when making use of the internal knowledge and solutions base.

A Novel Clone-Based Reuse Method to Maintain Proficiency in Software Engineering Practice

The source code of an application paves way for a quality software product. Quality software in-turn helps in imposing software reuse. In this paper, pieces of similar codes also known as code clones or code duplications are considered as reusable software components. In general code clones are considered harmful in software engineering practice. They are considered to degrade the quality of software. Code clones are detected and removed without further processing. In this paper, a token- based CodeClone reuse method is proposed to detect type1 and type-4 clones. Positive effects of clones are analyzed and beneficial clones are extracted from the cluster of clones detected. The proposed method aids in the art of developing software thereby enforcing the concept of software reuse. The working principle of the proposed method is implemented using open source software as inputs. Beneficial clones are further stored in a database for future use. Clone report is generated as it assists in knowing about the clone details within a software system.

AN ENERGY EFFICIENT WIRELESS BODY AREA NETWORK USING GENETIC ALGORITHM

In the proposed work, the main concern is to reduce the energy consumption while the node is in their working condition that is when the actual data transmission will take place. Other factor that we have considered is duty cycle. It is the time taken by the sensor nodes that operates irregularly rather than continuously. When the transmission distance is very small as compared to the threshold distance, duty cycle is very high and thus, there is no ideal time to recover charge for battery and hence, battery recovery effect is not considered. With the help of WBAN, the patient can be observed from remote station and the collected information by the bio sensor nodes attached to the patient will be transferred by using any wireless mean like LAN, WAN, Bluetooth, radio signal or electromagnetic waves. Also the collected information will be saved in the data base for future use. In the proposed work, we are designing a network area having length and width of size 1000×1000 along with 50 numbers of sensor nodes for different transmission distance changes from 50 -7500 for different bit rate. All the simulation process will be carried out in MATLAB environment and the performance parameters like Duty cycle, Energy consumption with baseline, offline and recovery algorithm will be measured along with optimization algorithm named as Genetic algorithm.

Completeness of data record in the obstetric record form

Objective: To survey the completeness of obstetric data records.Material and Method: A survey study was conducted to determine the completeness of obstetric data records of women who delivered at Songklanagarind Hospital from January 1, to June 30, 2012 in the obstetric data record forms of the Statistical Unit, Department of Obstetrics and Gynecology, Faculty of Medicine, Prince of Songkla University. The data consisted of 5 parts including general information, obstetric history, pregnancy outcome, complications andoperative obstetrics with indications. Rates of completeness by recorders were calculated.Results: A total of 1,698 obstetric data records were evaluated. The overall rate of completeness was 10.1%. The rates of completeness of the general information (part 1), recorded by nurses, and the clinical part (parts 2 to 5), recorded by physicians, were 36.7% and 26.1%. The intern had the highest rate of completeness, followed by the extern and the resident.Conclusion: The rate of completeness of obstetric data records was low. The feedback report will be sent to theDepartment of Obstetrics and Gynecology to find out an appropriate strategy to improve quality of electronic databasefor future use in research and quality service management.

Innovations in data collection, management, and archiving for systematic reviews.

Data abstraction is a key step in conducting systematic reviews because data collected from study reports form the basis of appropriate conclusions. Recent methodological standards and expectations highlight several principles for data collection. To support implementation of these standards, this article provides a step-by-step tutorial for selecting data collection tools; constructing data collection forms; and abstracting, managing, and archiving data for systematic reviews. Examples are drawn from recent experience using the Systematic Review Data Repository for data collection and management. If it is done well, data collection for systematic reviews only needs to be done by 1 team and placed into a publicly accessible database for future use. Technological innovations, such as the Systematic Review Data Repository, will contribute to finding trustworthy answers for many health and health care questions.

Quantitative Analysis of State Transportation Agency’s Experience with Constructability Reviews

The project development process aims to deliver the most appropriate roadway project given its context. Past work has shown that significant gains are realized when construction expertise is integrated early and throughout the project-delivery process. The Kentucky Transportation Cabinet has initiated a process that reviews design documents prior to construction to address issues that may result in time delays and cost increases. However, these efforts are not utilizing a systematic review process that would allow detailed documentation of the issues identified and provide a lessons-learned database for future use. The study undertaken classifies the constructability issues that typically impact highway construction projects. This paper first identifies the common constructability categories through a national review and then quantifies the frequency and severity of constructability issues by comment type and category, review year, reviewer, and comment severity. The paper’s primary contribution to the body of knowledge is the determination that constructability issues are dynamic and change over time, there is a need for consistency among reviewers, and that team reviews are more appropriate than a single-reviewer approach.

Validating the Impact on Reducing Fuel Consumption by Using an EcoDriving Assistant Based on Traffic Sign Detection and Optimal Deceleration Patterns

This paper implements and validates an expert system that, based on the detection or previous knowledge of certain types of traffic signals, proposes a method to reduce fuel consumption by calculating optimal deceleration patterns, minimizing the use of braking. The expert system uses a mobile device's embedded camera to monitor the environment and to recognize certain types of static traffic signals that force or can force a vehicle to stop. The system uses an adaptation of the algorithm proposed by Viola and Jones for the recognition of faces in real time, adapted to the detection of traffic signals. Detected signals are also incorporated into a central database for future use. When the vehicle approaches an upcoming traffic signal, the algorithm estimates the distance required to stop the vehicle without using the brakes, taking into account the rolling resistance coefficient and the road slope angle. Appropriate advice and feedback are provided to the driver to release the accelerator pedal. The expert system is implemented on Android mobile devices and has been validated using a data set of 180 tests with five different models of vehicles and nine different drivers. The main contribution of this paper is the proposal of an assistant that uses information from the environment and from the vehicle to calculate optimal deceleration patterns when approaching traffic signals that force or may force the vehicle to stop. In addition, the proposed solution does not require the installation of infrastructure on the road, and it can be installed into any vehicle.