TECHNOLOGY
Artificial Intelligence based Machine Learning with data, Optimization and Prediction
MOEV.AI™ is an always‑on AI/ML operations engine that ingests high‑frequency telemetry (vehicle CAN/telematics), CAD/AVL location and schedule data, enterprise asset and maintenance status, fuel and charging system telemetry (e.g., OCPP/utility meters), and external signals (tariffs, weather) into a unified, time‑synchronized data model. Streaming pipelines feed continuously updated predictive models that estimate usable range/energy, state‑of‑health, and time‑to‑ready for every bus. A real‑time optimization layer then computes—and can publish via open APIs—best‑fit vehicle‑to‑block assignments, charge start/stop and rate profiles to manage demand and TOU windows, and yard staging moves (parking bay + charger routing). Workflow engines sequence fueling, wash, and clean tasks; constraint logic enforces maintenance holds; anomaly detection flags wrong‑vehicle movements. The result is a data‑driven AI control architecture that coordinates charging, dispatch, and yard processes in real time.
Our technology is unique and it uses a combination of machine learning, deep learning, neural networks, regression, clustering, data science, dynamic optimization and several other AI and data science technologies to achieve these objectives. Our system operates on the Internet Cloud, is offered as a software as a service (SaaS), and is independent of all hardwares. For example, to interface with chargers, it uses the open protocol OCPP (MOEV.AI™ supports both Versions 1.6 and 2.01) standard, and for telematics connectivity, it is independent of the vehicle and connects by way of using an API (application programming interface).
The MOEV founders have been researchers and faculty members from UCLA Samueli School of Engineering from where the company was spun out, and, who collectively have deep technical expertise and knowledge in the field of electric vehicles, AI, Machine Learning and smart charging infrastructure, and have published over 300 technical publications/patents. All members of the technical team have a masters degree and half of them have PhDs in engineering/software/data science/etc.