Geolocalización Jobs

Global Ride-Hailing Platform — Project Description - (PREFER ONLY TO WORK WITH SOMEONE WHO ALREADY HAVE DONE IT) The Global Ride-Hailing Platform is a next-generation taxi technology ecosystem designed to operate at the same quality, reliability, and scalability standard as the world’s leading mobility platforms. The objective of the platform is to create a fully configurable, globally deployable ride-hailing infrastructure capable of launching in any city or country without requiring engineering changes or application redeployment. The platform is designed specifically for taxi and private hire transportation services and combines real-time dispatch intelligence, dynamic pricing, multi-market operations, and enterprise-grade infrastructure into a single unified system. It su...

We are looking for an experienced GIS and remote sensing specialist to generate a high-quality topographic map from LiDAR data. The freelancer should be able to process the point cloud data, create digital elevation models (DEM/DTM), and generate accurate contour lines. Please provide examples of your previous topographic mapping projects.

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I’ll provide raw LiDAR point-clouds and need you to turn them into presentation-ready topographic products—fast and flawless. Your workflow will start in Global Mapper (your stated preference) to import and classify the clouds, then continue through DEM generation, contour extraction, hillshade creation, and optional 3-D scene building. I review spot elevations against ground-control before sign-off, so accuracy down to the decimetre is essential. Deliver the first draft as soon as practicable; once I return comments, I expect a quick final turnaround. Deliverables • Clean DEM in GeoTIFF format • Contour lines (vector) • Hillshade raster • Lightweight 3-D model or scene file (any common format you support) • Print-quality PDF map and a fully...

Oportunidade: Desenvolvedor(a) Full-Stack (IA & Missão Crítica). Estamos selecionando desenvolvedor(a) para participar do projeto 'SAPCON - Sistema de Automação de Planos de Contingência'. O projeto já conta com um protótipo em 'Lovable'. O que você vai fazer:- Arquitetura de IA Multi-RAG: Implementar e otimizar um ecossistema de 5 camadas de RAG no Supabase Vector. - Orquestração de Processos: Refinar e escalar fluxos de automação no 'n8n', onde será executado o backend. - Desenvolvimento Full-Stack: Consolidar a interface em 'React/TypeScript' integrando com backend n8n, onde são executadas funcionalidades de geolocalização, roteamento,...

I am looking for a single experienced full stack developer to build an internal workforce and operations management application for my company. The app will initially be used only internally by our own team and is focused on mobile field workers in property management, facility service and concierge operations. I have already built and structured around 70% of the concept and workflow logic inside Base44, including user flows, features, operational structure and app behavior. I am now looking for a developer who can professionally turn this concept into a real working application and further improve and optimize the system together with me. The system should combine: • Mobile time tracking • Geofencing and GPS based customer recognition • Task and material tracki...

I’m planning a React Native app that must work totally offline yet still feel like a full-featured mapping and navigation tool. Before development begins, I need expert guidance on the best technical path to: • The app should detect and capture the user’s current geographic area. - Store map tiles locally for offline use. - Navigation with turn-by-turn directions • Drawing and recording polygons (think field boundaries or custom zones) • Attaching photos and precise coordinates to those saved shapes I’m open to any map data provider—as long as it’s reliable, can be bundled for offline use, and keeps ongoing costs low. During our session(s) I’d like to cover: – Recommended SDKs or libraries (e.g. Mapbox GL, React Native Ma...

AI-Orchestrated Hospitality ERP: Real-Time Worker Dispatch & Predictive Demand Logic ​The "Complicated" Core Requirements ​To solve this, a developer needs to master three distinct, overlapping domains: ​The Geo-Spatial Dispatch Engine: ​Instead of a static "ticket" system, the AI must calculate the "Cost of Service" based on a staff member's current location (GPS) and their active task queue. ​Complexity: Implementing a real-time proximity-based assignment algorithm that prevents "worker burnout" by balancing the load automatically. ​Predictive Staffing (The ML Layer): ​The system shouldn't just react to guests; it should predict them. It needs to ingest historical booking data, local weather APIs, and event calendars to forecast "...

AI-Orchestrated Hospitality ERP: Real-Time Worker Dispatch & Predictive Demand Logic ​The "Complicated" Core Requirements ​To solve this, a developer needs to master three distinct, overlapping domains: ​The Geo-Spatial Dispatch Engine: ​Instead of a static "ticket" system, the AI must calculate the "Cost of Service" based on a staff member's current location (GPS) and their active task queue. ​Complexity: Implementing a real-time proximity-based assignment algorithm that prevents "worker burnout" by balancing the load automatically. ​Predictive Staffing (The ML Layer): ​The system shouldn't just react to guests; it should predict them. It needs to ingest historical booking data, local weather APIs, and event calendars to forecast "...