RoboCalls has released it beta version. More features coming in future updates.
By coupling the capabilities of artificial intelligence (AI) and blockchain technology, Robocalls 2.0 will use its unique AI algorithm to scan through its user established and blockchain secured spam call ID database, to predict unwanted calls based on inbound dialing patterns. The structure relies on the Ethereum blockchain to validate, notify, and block this activity. Leveraging this powerful technology, our algorithm will create the biggest predicted black list database of unwanted and scam numbers in the blockchain.
Over 147 million mobile happen in United States per day. It is estimated that among this huge number of calls, 82 million are spam calls. This number is expected to reach 100 million by the end of 2019.
Several solutions have been designed to curb this menace in the communications industry but have been ineffective or failed entirely, either due to legal problems, hackability and caller ID spoofing, especially when it comes to previously proposed solutions such as Whitelisting/Blacklisting, Captcha and Crowdsourcing. An advanced method proposed to resolve this endemic challenge is to use intelligent real-time analysis techniques coupled with trusted big data to detect and apprehend these spam calls despite their complex change of identities.
By coupling the capabilities of artificial intelligence (AI) and blockchain technology, Robocalls 2.0 will use its unique AI algorithm to scan through its user established and blockchain secured spam call ID database, to predict unwanted calls based on inbound dialing patterns. The structure relies on the Ethereum blockchain to validate, notify, and block this activity. Leveraging this powerful technology, our algorithm will create the biggest predicted black list database of unwanted and scam numbers in the blockchain.
Over 147 million mobile happen in United States per day. It is estimated that among this huge number of calls, 82 million are spam calls. This number is expected to reach 100 million by the end of 2019.
Several solutions have been designed to curb this menace in the communications industry but have been ineffective or failed entirely, either due to legal problems, hackability and caller ID spoofing, especially when it comes to previously proposed solutions such as Whitelisting/Blacklisting, Captcha and Crowdsourcing. An advanced method proposed to resolve this endemic challenge is to use intelligent real-time analysis techniques coupled with trusted big data to detect and apprehend these spam calls despite their complex change of identities.
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What's New
Updating to meeting new requirements for google around sms and call logs
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Additional Information
Updated
January 23, 2020
Size
6.8M
Installs
1,000+
Current Version
1.5.7
Requires Android
7.1 and up
Content Rating
Everyone
Permissions
Report
Offered By
LazyMobile
Developer
970 Nolder Drive
Lancaster, Ohio 43130