Incentive Management (for merchant marketing compaigns), Reward Delivery System, and Distributed Biobehavioral Wallet for Cryptocurrencies
We illustrate a conceptual framework to add "incentives" to Bitcoin's four-sided network effect. Marc Andreessen noted that Bitcoin is a four-sided network effect consists of consumers, merchants, miners, and developers. Each side has a positive feedback loop (i.e., more population of each role will accelerate its growth). As we think more about current state of Bitcoin, about 450K user owns USD 100+ worth of Bitcoins. This ecosystem is still in its infancy. We would like to experiment a economic system that provides "incentives" among the four roles to grow the ecosystem. For example, one merchant may be interested in certain types of consumers; certain groups of consumers is seeking for specific merchant. Adding the ingredient of "incentives" may motivate more consumers and merchants to be part of this ecosystem.
There are a couple ways to understand a consumer's needs and where they are for merchants. Our preliminary solution is to take advantage of smartphone sensors and algorithms that are able to categorize consumer's behavioral pattern. It is merchant's job to define who their target customers are, however, this system can help merchants find consumers who fit into certain behavioral pattern. Now, we connect the consumers and merchants by providing a matching mechanism. Consumers are also miners who generate some share of cryptocurrency by doing a new type of proof-of-work. When a consumer performs certain behaviors, just like a miner doing proof-of-work, s/he can be rewarded for doing that behavior. This rewarding process notifies the merchant who is interested this type of behavior, so that the merchant is incentified to find their potential customers and pay the reward fee. Developes, who help find and define users' behavorial patterns, will also be awarded from this system.
Mobile crypto wallet is inevitable. Since Apple pulled the last crypto wallet app from the Appstore, crypto wallets could only exist as web wallets on iOS devices. This also implies Android (and maybe Ubuntu?) is going to become the major platform for crypto wallets in the near future. When smartphone hardware is going carry 10X+ of its value, security and anti-theft features are critical. There is a startup working on using ECG features with crypto wallet. This approach uses biometric identification as a way to validate wallet owner's control. This approach could be further extended with a concept of "distributed" wearable wallets.
Using a single wearble device to store and transact bitcoins can be unsafe if the biometric signing is unintentational. To increase the security, crypto wallet could consist of distributed wearable nodes signed by owner's biobehavioral data. These distributed nodes are doing Proof-of-Work (PoW) by collecting biosensing and behavioral data from the owner. Like Bitcoin's blockchain, these nodes store bio data just like Bitcoin's irreversible public ledger, but stored privately/distributedly on the wearable nodes. If one node left the owner, the other nodes can still doing PoW and the abandoned node is no longer valid to transact. This mobile/wearable-driven wallet approach may greatly increase the security of using crypto wallet.
Biobehaviorial information is sensitive to privacy and human rights. Behaviorial targeting is critical to all merchants. This project enables a new approach of accquiring and authenticating behaviorial information based on mobile sensing. Let's start by assuming this kind of information is privately stored, only accessible by its owner. Based on Bitcoin's blockchain's concept, we can structurally organize biobehavioral information and its ownership in a irreversible way. The base assumption is that the owner of the biobehaviorial information puts into efforts to maintain its information integraty in the most honest nature. A new type of proof-of-work is introduced here for linking ownership and biobehaviorial information. Owner does proof-of-work by labeling their information as claimning its ownership in the honest way. The labels need not to be very accurate. Biobehavioral information, such as ECG and accelerometer data, is signed with ownership with owner's private key and timestamp. By using one-label-one-vote, the majority vote decides the best label. As more biobehavioral information is accumulated, like bitcoin transactions are deeper in the blockchain, the labeled information becomes more trustworthy. This on-going labeling and data storage encourages machine learning techniques taken place in one's biobehaviorial blockchain as his/her personal app.