Smart Fleet Management System (FMS)
Smart Fleet Management System (FMS) is a solution to organize the fleet based on the real-time collection, analysis and optimization of the vehicles’ data. This system enables the managers and the drivers to track all the measurable data of the vehicle as well as suggestions and insights simultaneously. In Arshin, we have utilized some of the most advanced technologies in hardware and software so that both fleet managers and drivers can enjoy the benefits of our comprehensive, integrated and customizable system.
What benefits are we offering?
Arshin Smart Fleet Management System consists of two types of entering data i.e., smart sensors and entered-by-user data, intelligent analyzing process and output generation based on the user preferences. Real-time monitoring, workflow management and financial thrift are only a part of the valuable features that we offer to the fleets. Furthermore, our hardware devices and software modules are designed to develop an Internet of Behavior (IoB) platform by which the indicators of driving style can be generated and assessed out of the data. This specialty can be used in various management issues; from strategy and development to human resources and supply chain.
How do the IoT-based sensors helpful?
The sensors of IoT (Internet of Things) are becoming more and more common in all industries due to the multiplication of their capabilities. They enable the fleet managers and the drivers to monitor the important parameters of their cargo to preserve them under certain conditions. For example, the transportation of pharmaceuticals requires a consistent certain temperature at all times to avoid drugs corruption. Likewise, humidity level tracking is necessary for the distribution system of some edible material or decorative plants where a little tolerance may harm the quality. Or in alive cargos such as ornamental fish, where the whole package is domed if only a short dump occurs in the oxygen level. The IoT-based sensors can sense the data and send it to the server without hesitation via the internet. Therefore, the real-time conditions of the cargo are visible and trackable for the driver, the manager and the customer.
What is the added-value of tracking?
Nowadays, almost all drivers know how to use routing applications on their smartphone to find the fastest directions. Alongside that, tracking the vehicles of a fleet provides some other options for the manager such as geo-fencing, speed limitation, misuse and idling time. As the driving records are displayed and stored, the location of each vehicle is trackable at any time and the manager can enact some reward and punishment rules based on the drivers’ performance. Besides, in case of emergency, the tracking ability facilitates the process of finding the closest rescue forces (ambulance, fire engine or police) and navigating them towards the victim’s location.
User-based entering data
Not all the entering data come from the sensors. Sometimes, the data entered by the panel users are as valuable-to-track as that of the sensors. The managers can enter mission instructions and details, and set up customized workflows and forms for each vehicle. Likewise, the drivers would be able to eliminate paperwork and enter the delivery data as well as maintenance information in their panel. So, all the workflows are followable and all the services are registered so that the system notifies when it’s time to check them again.
Big Data Analysis
As all these data pile up together, they become harder to track even though they might contain more important insights. For example, assessment of the service providers and material suppliers can be so valuable for a big fleet like internet-based taxis. They should know whether the promotions offered by the supplier are worthy or not in comparison to the performance their product gave. An engine oil or a brake pad might be at half price but doesn’t worth as its useful life is even less than half of another one. We can extract useful information and insight by using Data Mining methods. Consequently, the user-based and sensor-based data together will provide us with insightful results such as supplier assessment, fuel theft reduction and road quality evaluation. These insights can be used by businesses to save more money and by the government to make correct policies.
How can AI help the analysis process?
Knowing that data analysis and insight creation requires so much time and energy, we developed Artificial Intelligence (AI) to help the managers get insights from their fleet’s data. It uses specialized algorithms to gather two categories of data, user-based and IoT-based, together, compares them to each other, refines them, and create managerial insights out of them. For instance, the AI can merge overall delays, service cost, useful life, etc. and create a maintenance provider reliability criterion for preventive maintenance. Or it can integrate the map layer database such as terrific and terrain, with the tracking data such as sudden braking or spiral movement to present a driving risk parameter based on the records. These insights can help businesses to evaluate their fleet accurately and save money on the insurance negotiations, without having to hire data scientists.
