SKU: 81347408052

LockMaster Swing Gate Opener Auto 40W Solar Power Electric Remote Control 800KG

$170.52 $189.47
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Description

LockMaster Swing Gate Opener Auto 40W Solar Power Electric Remote Control 800KGIf you find opening and closing your front gate is a hassle, then the Lockmaster Automatic Swing Gate Opener is just the thing you need. Designed to work with gates of up to 5. 5m wide and each weighing 400kg, the automatic swing gate opener is operated by a powerful 24V 80W DC motor that runs off power from the mains. However, you can also use the supplied 40W polycrystalline solar panel to use solar power as backup. Two 12V 7Ah batteries are also

If you find opening and closing your front gate is a hassle, then the Lockmaster Automatic Swing Gate Opener is just the thing you need. Designed to work with gates of up to 5.5m wide and each weighing 400kg, the automatic swing gate opener is operated by a powerful 24V 80W DC motor that runs off power from the mains. However, you can also use the supplied 40W polycrystalline solar panel to use solar power as backup. Two 12V 7Ah batteries are also supplied as further backup power. In essence, there is ample energy to work the gates in the event of any power outage. A manual release key is also included. Not least, the swing arms are made of high quality aluminium and designed for heavy duty performance as well. All components are housed in a weatherproof control box and three remote controls are provided that operate within a 30m range. There is also a stop and reverse mode with the controls. All necessary hardware for installation and an easy-to-follow set up manual and DVD are supplied together with your purchase.

Features
Two swing arms for use with double gates
Gates up to 5.5m in width and 400kg in weight per arm
2 x 12V 7Ah backup batteries
40W polycrystalline solar panel
Waterproof and dustproof control box
Low power consumption
24V low voltage system
High-quality aluminium swing arm
Stop and reverse mode for obstructions
Emergency release key
2 remote controls w/ 30m operation range
Full user manual and DVD included
Installation hardware

Specifications:
Voltage: DC 24V
Input: 230V/50Hz or 120V/60Hz
Solar Panel: 40W
Power: 50W/arm
Gate weight: 400kg (per arm)
Gate width: 5.5m
Current: 3A
Actuator speed: 16mm/s
Actuator travel: 385mm
Protection class: IP44
Power supply: Solar energy / Electri
Assembly Required: Yes
Backup battery: 2X 12V 20AH AGM Battries
Remote control battery: Alkaline zinc manganese battery 12V 27A
Please note: This item comes in 2 Packages

Package Content
(1) Gate Opener arm x 2
(2) Solar Panel x 2
(3) Control Box x 1
(4) User Manual x 1
(5) Remote Control x 2
(6) Installation Accessories x 1

This product comes with 1 year warranty.

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
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Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
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SKU: 81347408052

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4.6 ★★★★★
Based on 9 reviews
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Product Reviews
O
Om S
Pawtucket, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Birmingham, US
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity. What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike. Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
N
Nader
West Palm Beach, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
West Palm Beach, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
Lexington, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025

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