Automated Tote Counting Camera System

@Mahihassi

As an AI and Cloud Developer with a keen understanding of backend systems, I am confident in providing the robust, reliable solution you're seeking for your tote counting needs. My rich expertise in Computer Vision and Deep Learning can be instrumental in tackling the challenges posed by low light, occlusion, and rapidly moving objects. Throughout my career, I have proactively devised strategies to handle similar situations, ensuring accurate results. Appreciating your preference for on-device or edge processing, I commit to leveraging my skills to create an efficient system that minimizes data usage while optimizing performance. In line with your demand for high-resolution frames that facilitate individual tote identification under variable lighting conditions, I'm adaptable to utilizing standard optical technology coupled with night vision or even infrared approaches if deemed more suitable. My proficiency extends beyond just software development and encompasses hardware integration as well. I'll deliver a comprehensive package, including a detailed bill of materials with part numbers and sourcing information for 100 units. Furthermore, my capability in designing resilient camera mounts using CAD will ensure stability in vibration-laden scenarios while considering the necessity of wash-downs.

@ZohaibRoy

⭐⭐⭐⭐⭐ Create an Automated Counting System for Your Truck Fleet ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project requirements and see you are looking for a camera-based solution to count plastic totes in your refrigerated trucks. You have no need to look any further as Zohaib is here to help you! My team has completed over 50 similar projects in logistics automation. I will create a robust system that functions in challenging loading dock conditions, ensuring accurate counting without disrupting the workflow. ➡️ Why Me? I can easily build your automated counting system as I have 5 years of experience in image recognition and logistics solutions. My expertise includes camera technology, software development, and data management. Not only this, I have a strong grip on edge processing and SQL integration, ensuring a seamless and efficient system for your trucks. ➡️ Let's have a quick chat to discuss your project in detail and let me show you samples of my previous work. Looking forward to discussing this with you in chat. ➡️ Skills & Experience: ✅ Image Recognition ✅ Camera Technology ✅ Software Development ✅ Data Management ✅ Edge Processing ✅ SQL Integration ✅ System Design ✅ User Manuals ✅ Hardware Sourcing ✅ Pilot Testing ✅ Troubleshooting ✅ Project Management Waiting for your response! Best Regards, Zohaib

@Softeria

As a seasoned computer vision expert with over 12 years of experience in AI software development, I'm the perfect candidate for your automated tote counting camera system. I have successfully led and delivered over 600 projects, many of which involved AI automation and LLM applications just like the one you are seeking. With regard to the technical challenges you've mentioned, I have extensive experience handling similar issues. My AI systems incorporate robust computer vision algorithms that can distinguish individual items even under varying lighting conditions, occlusion, and rapid movement. Additionally, my proficiency in data processing will ensure that each step of the counting process is accurately logged in real-time and will seamlessly integrate with your existing SQL back-end. I understand that as vital as the software is, its proper integration into hardware and efficient deployment are equally important. My proven ability to manage all aspects of your project from end to end will guarantee a smooth process and successful outcome. Moreover, my vast network with leading suppliers in the industry enables me to swiftly source the best quality materials necessary for your 100 units while keeping costs in check. Ready to get started on building an efficient automated system for your fleet!

@umg536

Hello, This is a very strong use case for an edge-AI vision system, especially because the environment is uncontrolled and the driver workflow cannot be interrupted. The main challenge here is maintaining reliable tote separation and directional tracking under low light, occlusion, vibration, and stacked movement, which is something we already account for when designing industrial vision systems. My recommendation would be a rugged dual-camera setup with onboard AI processing inside each truck using industrial low-light cameras and edge inference hardware such as NVIDIA Jetson. This approach keeps bandwidth low while allowing accurate real-time IN/OUT counting even when drivers temporarily block the view or totes move in stacks. I can handle the complete solution including hardware selection, camera mount CAD design, AI model training, API integration with your SQL backend, deployment packaging, pilot installation, and fleet rollout preparation for all 100 trucks. The project would normally be divided into a prototype phase, a live pilot on one truck for model tuning and accuracy validation, followed by full deployment preparation once the ≤1% error target is verified during live operation. I’d be happy to discuss the recommended camera layout, processing architecture, and the most reliable approach for handling stacked totes and difficult lighting conditions inside refrigerated trailers.

@juanjosec63

Hi, I've done the same camera work before so I can explain about the whole process how it works. I have gone through your project description and understand you’re looking to build a camera-based tote counting system for refrigerated trucks that can accurately track totes moving in and out in real loading dock conditions without affecting driver workflow. I have worked on computer vision and edge AI systems using object detection models, industrial cameras, embedded devices, and API-based data transfer. I also have experience handling low light conditions, object occlusion, and real-time tracking systems. For this, I would build an edge-based counting system using industrial cameras with IR/night support and a trained detection model to count stacked totes accurately. The system would process counts locally and send IN/OUT data with timestamps and truck IDs directly to your SQL API. Best regards, Juan

@OscarMozo

Hi, I can help you You want a plug-and-play camera setup that counts every tote going in and out of each truck, day or night, even with people blocking the view and totes stacked. It should not slow drivers, mount out of the way, work on the truck’s power, process on the edge, and send simple count records to your SQL API. We’ll deliver hardware list, mount design, trained software, guides, and a pilot that proves under 1 percent error. This will take a few days, I've been doing this type of work for years. I have short walkthrough videos on my Freelancer profile showing similar work. 1) What do you have now for mounts, power access, and cellular connectivity per truck? 2) What should the final dashboard or report look like for IN, OUT, time, and truck ID? Ideally, we have a call and go through the details together so I can make sure I understand everything correctly, address any questions, and give you a quote and timeline. Would that work? Best, Nicolas

@tangramua

Hello! We have worked on camera-based recognition and counting solutions for logistics and warehouse operations, where items move in stacks, pass through constrained spaces, and must be detected without disrupting human workflow. We are comfortable taking full ownership of a turnkey solution: selecting the right camera technology for low light and high contrast conditions, designing a vibration-resistant mount, implementing edge-based image processing for tote detection and separation and transmitting structured IN/OUT events to your existing SQL backend via the provided API. We also have experience preparing hardware BOMs for multi-unit deployments, creating repeatable installation guides, and validating accuracy through real pilot runs before scale-up. Handling stacked objects, temporary occlusion by drivers, and variable lighting are challenges we have solved before in vision-based tracking scenarios. We would be glad to review your truck layout and door geometry to propose the optimal camera position and processing architecture, and to outline a clear timeline for prototype, pilot validation and full fleet deployment. Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews. Please contact us via Freelancer Chat to discuss your project in details. Best regards, Kateryna Sales department Tangram Canada Inc.

@mobasherreza10

Hi there, I see you need a camera based tote counting system for 100 refrigerated trucks that works in variable lighting, handles driver occlusion and stacked totes, with zero driver interaction. I recently deployed a similar vision system for a logistics company using IR cameras and edge based YOLO tracking, achieving 99.2% accuracy across challenging loading dock conditions with lighting from bright sun to total darkness. I would love to do the same for your fleet. My approach uses an IP68 IR camera with on truck Jetson Orin Nano for edge processing, temporal tracking to handle occlusion, and edge detection to separate stacked totes. I will deliver a hardware BOM for 100 units, mounting CAD, trained software, installer guide, and a pilot on one truck proven at ≤1% error before full rollout. Timeline is 4 weeks to pilot, 2 weeks validation, then scale. Best regards, Mobasher Reza