Abstract: Both daily and long-term management of a heavy-duty vehicles and construction machinery fleet is an extremely complicated and hard to solve issue. This is mainly due to the diversity of the fleet vehicles – machinery, which concerns not only the vehicle types, but also their age/efficiency, as well as the fleet volume, which is often of the order of hundreds or even thousands of vehicles/machineries. In the present paper we present “InteligentLogger”, a holistic heavy-duty fleet management system covering a wide range of diverse fleet vehicles. This is based on specifically designed hardware and software for the automated vehicle health status and operational cost monitoring, for smart maintenance. InteligentLogger is characterized by high adaptability that permits to be tailored to practically any heavy-duty vehicle/machinery (of different technologies -modern or legacy- and of dissimilar uses). Contrary to conventional logistic systems, which are characterized by raised operational costs and often errors, InteligentLogger provides a cost-effective and reliable integrated solution for the e-management and e-maintenance of the fleet members. The InteligentLogger system offers the following unique features that guarantee successful heavy-duty vehicles/machineries fleet management: (a) Recording and storage of operating data of motorized construction machinery, in a reliable way and in real time, using specifically designed Internet of Things (IoT) sensor nodes that communicate through the available network infrastructures, e.g., 3G/LTE; (b) Use on any machine, regardless of its age, in a universal way; (c) Flexibility and complete customization both in terms of data collection, integration with 3rd party systems, as well as in terms of processing and drawing conclusions; (d) Validation, error reporting & correction, as well as update of the system’s database; (e) Artificial intelligence (AI) software, for processing information in real time, identifying out-of-normal behavior and generating alerts; (f) A MicroStrategy based enterprise BI, for modeling information and producing reports, dashboards, and alerts focusing on vehicles– machinery optimal usage, as well as maintenance and scraping policies; (g) Modular structure that allows low implementation costs in the basic fully functional version, but offers scalability without requiring a complete system upgrade.
Abstract: This paper may be considered as combination of both pervasive computing and Differential GPS (global positioning satellite) which relates to control automatic traffic signals in such a
way as to pre-empt normal signal operation and permit lifesaving vehicles. Before knowing the arrival of the lifesaving vehicles from
the signal there is a chance of clearing the traffic. Traffic signal
preemption system includes a vehicle equipped with onboard computer system capable of capturing diagnostic information and
estimated location of the lifesaving vehicle using the information provided by GPS receiver connected to the onboard computer system
and transmitting the information-s using a wireless transmitter via a
wireless network. The fleet management system connected to a
wireless receiver is capable of receiving the information transmitted
by the lifesaving vehicle .A computer is also located at the
intersection uses corrected vehicle position, speed & direction
measurements, in conjunction with previously recorded data defining
approach routes to the intersection, to determine the optimum time to
switch a traffic light controller to preemption mode so that lifesaving
vehicles can pass safely. In case when the ambulance need to take a
“U" turn in a heavy traffic area we suggest a solution. Now we are
going to make use of computerized median which uses LINKED
BLOCKS (removable) to solve the above problem.