SAFEJACK - A SMART PROTECTOR

Abstract

SAFEJACK- A SMART PROTECTOR ABSTRACT SAFEJACK - A SMART PROTECTOR revolutionizes construction site safety and efficiency by integrating Internet of Things (loT). and Artificial Intelligence (AI) technologies. This project is an advanced safety and project management solution for construction sites, integrating sensor-enabled safety jackets, real-time data visualization, and 3D model comparisons to enhance worker safety and streamline project oversight.The safety jackets are equipped with multiple sensors that monitor workers' vital signs, location, and environmental conditions. Data from these jackets is transmitted to a centralized dashboard, where stakeholders cau view real-time safety metrics, enabling timely interventions and personalized safety recommendations to protect workers in hazardous settings.The dashboard also features a 3D model comparison tool, which overlays real-time images from the construction site onto the original design model to provide a precise, visual representation of project progress. This comparison of 3D visualizations empower project stakeholders to make informed, immediate decisions that optimize worknows. impro·/e safety measures, and drive quality assurance and also to monitor work completion levels accurately and identify any deviations from the original plan. With real-time hazard detection. proactive accident prevention, and AI-driven quality control, SAFEJACK establishes a safer, more efficient construction environment that elevates industry standards in safety and operational productivity.Through this multifaceted approach, SAFEJACK establishes a safer work environment, enhances project management efficiency, and sets new standards for safety and resource optimization in construction field.

Specification

FIELD OF INVENTION:
A "field invention" refers to a novel development within a specific area of study. SAFEJACK
relates to the integration of Internet of Things (loT) devices and Artificial Intelligence (Al)/Machine
Learning (ML) tools for real-time construction project management. Key innovations involve
creating an industry-standard dashboard that monitors progress, resource usage, safety, and quality
metrics. enabling data-driven decision-making. The system includes Al-powered defect recognition,
real-time hazard detection, and LIDAR based picture monitoring .This invention is poised to
revolutionize project management, improving efficiency, safety, and quality in the construction
industry.
BACKGROUND INVENTION:
[001]
AUTHOR NAME: Yasusato Fujieda, Hisashi Matsumoto
PATENT NO: US I 055634282
DESCRIPTION: A teaching device constructs, in a virtual space, a virtual robot system in which a
virtual 30 model of a robot and a virtual 30 model of a peripheral structure of the robot are arranged,
and teaches a moving path of the robot. The teaching device includes an acquisition Lwit configured
to acquire information about a geometric error between the virtual 30 models, and a correction unit
configured to correct the moving path of the robot in accordance with the information acquired by-the
acquisition unit.
[002]
AUTHOR NAME: Justin J. Ploeger!, Dominick James O'Dierno ,Brian Scott Otto
PATENT NO:US20210200792A I
DESCRIPTION: A building system of a building including one or more memory devices having
instructions thereon, that, when executed by one or more processors, cause the one or more
processors to retrieve projection rules for generating a building graph projection. The instructions
cause the one or more processors to retrieve a plurality of entities representing clements of the
building and a plurality of relationships between the plurality of entities representing relationships
between the plurality of entities, construct the building graph projection including a plurality of nodes
and a plurality of edges based on the plurality of entities, the plurality of relationships, and the
projection rules, and perform one or more operations based on the building graph projection.
[003]
AUTHOR NAME: Alberto Giovanni Bonomi , Christian Andreas Tiemann , Wei Chen
PATENT NO: US20 180 192914A I
DESCRIPTION:Methods and systems for monitoring metabolic parameters of humans and other
animals in an enclosed or semi-enclosed space such as a room. In these embodiments, metabolic
parameters like basal metabolic rate, energy expenditure, and body composition are derived from
environmental measurements of carbon dioxide (C02) production using context-aware processing
algorithms. This information can be integrated in innovative coaching programs for weight
management, fitness improvement, pregnancy management, and chronic disease management.
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[004]
AUTHOR NAME: Dhairya Shrivastava , Stephen Clark Brown , Vijay Mani , Ronald F. Cadet
PATENT NO:USII68704582
DESCRIPTION:Discloscd arc platforms for communicating among one or more otherwise
independent systems involved in controlling functions of buildings or other sites having switchable
optical devices deployed therein. Such independent systems include a window control system and
one or more other independent systems such as systems that control residential home products (e.g.,
thermostats, smoke alanns, etc.), HVAC systems, security systems, lighting control systems, and the
like. Together the systems control and/or monitor multiple features and/or products, including
switchable windows and other infrastructure of a site, which may be a commercial. residential. or
public site.
[005]
AUTHOR NAME: Albert Holaso
PATENT NO:USI003149482
DESCRIPTION:A system and approach having a display that shows a dashboard of smart buttons or
tiles. The smart buttons or tiles may be situated in a matrix-like or other arrangement on the
dashboard. The display may be customized. A smart button or tile may be operated like a standard
button but conveniently pull summary information about a particular area of, for instance, a building
controls system, for a user. The arrangement may permit the user to view the health of the whole
system at a glance and permit the user a shortcut to see details of the particular area of the system
quickly.
OBJECTIVES :
i) Enhance Worker Safety Through Real-Time Monitoring
Utilize sensor-equipped safety jackets to cominuously monitor workers' vital signs, location,
and environmental conditions, enabling real-time hazard detection and immediate intervention in
hazardous settings.
ii) Centralize Safety and Project Data Visualization
Develop a centralized dashboard for stakeholders to access live safety metrics, environmental
conditions, and personalized safety recommendations, facilitating timely responses to potential
safety threats.
iii) Optimize Project Oversight with 3D Model Comparisons
Implement a 3D model comparison tool to overlay real-time images from the construction site
onto the original design model, helping stakeholders assess project progress and accurately track
work completion levels.
iv) Enable Proactive Hazard Detection and Accident Prevention
Integrate loT and AI technologies for early hazard detection and proactive accident prevention,
minimizing risks associated with hazardous construction environments.
v) Drive Quality Control with AI-Driven Insights
Utilize AI-driven analytics to continuously assess quality, identify deviations from design
specifications, and ensure adherence to safety and quality standards throughout the project
lifccycle.
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vi) Improve Decision-Making for Workflow Optimization
Provide stakeholders with accurate, up-to-date data to make informed decisions on project
workflows, enhancing opcrotional productivity and resource management.
SUMMARY:
SAFEJACK is a Smm1 Protector that aims to transfmm construction project management by
integrating loT devices and AI/ML tools into a comprehensive dashboard for real-time monitoring.
The system provides live updaies on progress, safety, resource usage, and quality metrics, enabling
data-driven decisions and improved productivity. Key features include real-time hazard detection,
AI-enabled defect recognition and resource optimization. Additionally, the dashboard offers 30
model generation by comparing photographs with original models for enhanced analysis. The project
ensures safer, more efficient construction processes while enhancing quality control.
BRIEF DESCRIPTION OF DRAWING:
Figure 1 : Model Safety Jacket for Construction Workers
Figure 2 : Framework of the Project
DETAILED DESCRIPTION OF THE INVENTION :
SAFEJACK is an advanced safety and project management solution designed specifically for
construction sites. By integrating cutting-edge technologies such as Virtual Reality (VR), Internet of
Things (loT), and Artificial Intelligence {AI), SAFEJACK aims to enhance worker safety and
optimize project oversight. This innovative system incorporates sensor-enabled safety jackets, a
centralized data dashboard, and a. 30 model comparison tool to create a safer and more efficient
construction environment.
Key Features and Functionality
i) Real-Time Monitoring:
SAFEJACK employs sensor-equipped safety jackets that continuously monitor workers' vital
signs, location, and environmental conditions. This data is transmitted in real-time to a centralized
dashboard, allowing for immediate hazard detection and timely intervention. By maintaining
continuous surveillance, the system enhances labor safety, reduces the risk of accidents, and fosters a
safer work environment. Workers can feel more secure knowing that their health and safety arc being
actively monitored.
ii) Centralized Data Visualization:
The centralized dashboard provides stakeholders with live access to safety metrics and
environmental conditions on-site. This feature enhances transparency and facilitates timely responses
to potential safety threats, ensuring proactive management of any emerging issues. By aggregating
data in one accessible platform, stakeholders can quickly identify trends or anomalies, making it
easier to implement necessary adjustments and improve overall site safety.
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iii) 3D Model Comparison Tool:
SAFEJACK's 30 model comparison tool overlays real-time images from the construction site
onto the original design model. This capability enables stakeholders to accurately assess project
progress and track work completioP. levels against the planned timeline. By identifying deviations
from the project plan as they occur, stakeholders can make informed decisions that optimize
workflows and enhance project management efficiency, ultimately leading to better resource
allocation and adherence to schedules.
iv) Proactive Hazard Detection:
Integrating loT and AI technologies, SAFEJACK facilitates early hazard detection and proactive
accident prevention. The system continuously analyzes data to pinpoint potential risks in the
construction environment, which helps to minimize the likelihood of accidents. By identifying
hazards before they escalate, the system ensures that safety measures can be implemented promptly,
contributing to a safer workplace for all personnel.
v) AI-D riven Quality Control:
Al-driven analytics play a crucial role in continuously assessing quality throughout the project
lifecycle. SAFEJACK identities deviations from design specifications and ensures that safety
standards are maintained. By supporting effective quality control, the system enhances project
outcomes and minimizes costly errors or rework, leading to increased stakeholder confidence and
satisfaction with project deliverables.
vi) Informed Decision-Making for Workflow Optimization:
SAFEJACK empowers stakeholders with accurate, up-to-date data, enabling them to make
informed decisions regarding project workflows. This data-driven approach enhances operational
productivity and resource management by providing insights into performance metrics and project
status. As a result, stakeholders can identify areas for improvement and implement strategies that
drive overall project efficiency and effectiveness, ensuring that resources are utilized effectively to
meet project goals.
vii) Automated Emergency Response Activation :
In case of accidents, such as falls or exposure to harmful substances, SAFEJACK can
automatically activate an emergency response protocol. This includes notifying on-site managers,
safety personnel, and nearby medical teams. Automated responses improve reaction times, ensuring
that injured workers receive assistance as quickly as possible.
viii) Geofcncing and Restricted Zone Alerts :
Using geofencing technology, SAFEJACK can create virtual boundaries around hazardous or
restricted areas on the construction site. If a worker approaches or enters these zones, the system
triggers an alert to notify supervisors. This feature prevents unauthorized access to high-risk areas,
protecting workers from potential harm and ensuring that only qualified personnel enter these zones.
ix) Environmental Monitoring and Alerts :
SAFEJACK can include sensors to monitor environmental factors like temperature, humidity, air
quality, and noise levels. If any of these factors exceed safe thresholds, the system sends immediate
alerts to supen·isors and workers, allowing them to take necessary precautions to prevent health risks
due to exposure to hazardous conditions.
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x) Fatigue Detection System :
Al-powered algorithms can analyze biometric data, such as heart rate variability and movement
patterns, to detect signs of worker fatigue. When fatigue is detected, SAFEJACK can alert
supervisors, prompting rest breaks or reassignment to prevent accidents caused by exhaustion and
improve overall productivity and worker well-being.
xi) Mobile Access for On-Site Supervisors :
A mobile app version of SAFEJACK's dashboard could allow on-site supervisors to access safety
and project data directly from their sma11phones or tablets. This mobile access enables them to make
immediate decisions, log incidents, and check on workers' conditions without needing to be at a
desktop station, increasing the system's flexibility and responsiveness.
xii) Weather-Integrated Safety Alerts :
SAFEJACK could be integrated with weather data to provide alerts related to weather conditions
that might affect worker safety, like storms, high winds, or extreme temperatures. This feature
enables supervisors to plan activities around weather risks and prevent exposure to dangerous
weather conditions, ensuring both worker safety and site productivity.
xiii) Predictive Maintenance for Equipment :
SAFEJACK can integrate with loT sensors attached to construction equipment to monitor their
condition continuously. Predictive maintenance analyzes usage patterns, vibration levels, and other
indicators to forecast when equipment might require servicing, preventing unexpected breakdowns,
reducing repair costs, and enhancing on-site safety.
xiv) Personalized Safety Recommendations :
SAFEJACK can leverage historical data and machine learning to deliver tailored safety
recommendations for each worker, based on their past health metrics, work history, and
etwironmental exposure. Personalized recommendations help optimize worker safety, suggesting
specific protective measures, adjustments in schedules, or task rotations to reduce risk.
xv) Data Privacy and Security Measures :
Since SAFEJACK handles sensitive data, it could inciude advanced data privacy and security
features such as encrypted data transmission, role-based access controls, and compliance with
industry regulations like General Data Protection Regulation (GDPR). This feature ensures that
workers' personal inforn1ation is secure and that the data is only accessible to authorized personnel.
xvi)Technological Specifications :
SAFEJACK integrates loT, LiDAR, and AI technologies to monitor worker safety and
construction progress in real-time. ARJVR overlays, ML-trained algorithms, and multi-sensor jackets
provide predictive safety insights, while geolocation and AI anomaly detection ensure accurate
project oversight. This innovative solution elevates safety and operational efficiency in construction
environments.
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CLAIMS
WE CLAIMS
Claim 1: A multi-sensor enabled safety jacket integrated with loT technology monitors workers' vital
signs (e.g., heart rate, body temperature), location, and environmental conditions (e.g., air quality,
temperature) on construction sites. The sensors collect real-time data and transmit it to a centralized
dashboard for continuous monitoring and intervention.
Claim 2: Building on Claim 1, a real-time multi-modal data fusion algorithm integrates multiple data
streams from the wearable safety jackets, environmental sensors, and 3D site images. This allows for a
holistic assessment of worker safety, detecting issues like heat exhaustion risks, air quality
deterioration, and progress in construction activities.
Claim 3: As outlined in Claim 1, the sensors embedded in the safety jacket provide time-series data,
which is processed by an AI-powered predictive safety risk detection system. This system forecasts
potential accidents, such as falls or heat strokes, by analyzing trends in workers' vital signs and
environmental changes (e.g., rapid temperature rises or oxygen depletion).
Claim 4: Complementing Claim 2, a real-time 3D model comparison tool overlays site images with the
original design model to track construction progress. The system detects deviations in structural
alignment, placement of materials, and component installations, sending real-time alerts to
stakeholders for corrective action. For example, it flags when walls are misaligned with the design or
when equipment is placed incorrectly.
Claim 5: As indicated in Claim 3, an At-driven safety recommendation system provides personalized,
real-time interventions for workers based on their vital signs and site hazards. For example, if a
worker's heart rate spikes in a high-temperature area, the system will recommend hydration or
suggest moving to a cooler location. It adapts dynamically to each worker's health data, alerting them if
they are overexerted or exposed to hazardous conditions.
Claim 6: Expanding on Claim 1, a geolocation-based monitoring system continuously tracks worker
movements. It provides real-time location data to ensure workers do not enter hazardous or restricted
zones, such as areas with heavy machinery or unstable structures. If a worker breaches a restricted
area, the system triggers immediate alerts to both the worker and the site supervisors.
Claim 7: As part of the overall safety management system, an encrypted in-app communication feature
allows workers and managers to securely exchange information. Workers receive real-time alerts
about safety hazards (e.g., air quality alerts or structural instability warnings), while managers can
provide immediate feedback and guidance, all while maintaining data privacy.
Claim 8: Enhancing project oversight, a fraud detection sysLe111 within the project management
module (referenced in Claim 1) uses AI-based anomaly detection to compare real-time 3D models
against the original design. This system identifies discrepancies in progress reports, preventing
fraudulent claims such as inflated completion percentages or misreported work quality by flagging
misalignments between design and reality.
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Claim 9: A centralized safety dashboard (introduced in Claim 1) aggregates data from wearable
sensors, environmental monitors, and 30 visual tools, displaying real-time safety metrics such as
worker health trends, hazardous zone activity, and construction progress. This dashboard uses
Al-generated insights to help stakeholders make informed decisions, such as reallocating workers to
safer areas or addressing construction delays caused by environmental factors.
Claim 10: Extending Claim 4, a 30 visual comparison system evaluates real-time project progress by
comparing live site visuals with..30 architectural models. The system can detect misalignments instructural
elements, such as beams or columns, and also allows for customizable adjustments in design
features like wall colors, window place-ments, or material choices, ensuring both safety and design
compliance.
Date:

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