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IOTIFY- a Rapid Prototyping Tool for Building IoT Systems

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IOTIFY- a Rapid Prototyping Tool for Building IoT Systems

Dear Hackers, One of the most common problem when creating IoT solutions is to build something starting from scratch. There are plenty of great cloud platform providers out there, however, we have observed that currently there are no easy ways to simulate an entire IoT system. The dependency upon hardware and sensors make it even more complex to work out a proof of concept and showcase a viable end to end solution. At iotify.io we have built tools which will help you prototype a large-scale IoT solution with ease - working with cloud provider of your choice. The Database generator could generate a large amount of Sensor data based upon the template you specify and save it into a JSON file or inject it directly to MongoDB/ElasticSearch (any many databases in the future). The idea here is to quickly get you started with offline sensor analytics. You could write custom functions and control the pattern completely. Network Simulator (coming soon) generates real-time traffic from thousand of IoT nodes (MQTT/HTTP and many other in future) in a similar way, thereby simulating a live IoT system. It would be very useful for stress testing your solution as well doing some real time analytics. Virtual IoT lab allows you to play with different hardware and sensor projects which are completely virtual and programmable in your browser, thereby allowing you to prototype PoC quickly. We will be working to make more boards and sensors available in the future. We are looking forward to hearing what do you think of these tools and any other ideas which we should focus on. Please signup at iotify.io and give it a try. Please contact us if you run out of limits of a free version and we would be happy to upgrade. TIA Akash & Sebastian

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
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Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released
67%67% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform, soon · Missing: plus, intuitive, reviews
42%42% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: way · Missing: mobile apps, ios, personal
39%39% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Product HuntUnlikely to reach the leaderboard · Missing: mac, agents, macos
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Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
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BetaListMay not resonate with beta-testers · Strong signals: real time · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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