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Jumptuit Transport and Logistics

 Jumptuit Transport and Logistic’s (J2T-TL) mission is to protect people and goods in transit, improve the health and well being of workers, and increase public safety in harmony with the environment. J2T-TL provides AI-powered cross-sector scenario forecasting for any geolocation to optimize scheduling and routing, mitigating delays, property and personal safety risk, public health and safety conditions, and carbon emissions.

 

J2T-TL continuously calculates the optimal time of departure for each scheduled route for each vehicle in a fleet, minimizing the potential number of incidents, travel time, consecutive driving hours per driver, and carbon emissions. AI-powered scenario forecasting of cross-sector conditions and exposures makes it possible for an organization with a large fleet of vehicles to reduce the number of occurring incidents and ensuant claims with a high level of confidence.

 

Jumptuit’s Event Genesis Intelligence (EGI) identifies the time and place of future events and generates adaptive scenario forecasting based on continuous analyses of Real-Time-Cross-Spectrum-Data (RTCSD) captured via Jumptuit’s Global Data Nets (GDNs).

 

By more accurately forecasting and reducing the number of consecutive driving hours per route, J2T-TL enables organizations to meet FMCSA Department of Transportation regulations and improve working conditions for drivers. Continuous optimization of vehicle departure schedules enables large fleet carriers to systematically reduce the actual number of pounds of carbon emissions per route for each vehicle and provide auditable carbon emissions reports.

 

Origin, route, and destination dynamic geolocation scenario forecasts consider the impact of a combination of factors, including conditions in hazard zones, climate emergencies, potential infrastructure failures, weather advisories, carbon emissions, energy consumption, and regulatory compliance.

 

Dynamic geolocation scenario forecasts also consider the impact of exposures to assess driver health risk, including the combined effect of viruses (e.g., airborne, contact, and environmental), contamination, and environmental conditions, as well as proximity to emergency healthcare services and resources (e.g., hospitals, ICU bed availability, and urgent care facilities).

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