Energy reward computation for smart homes

You need to compute financial rewards reading data from different sources (databases, APIs and MQTT brokers), the computation has to run on servers, mobile, on embedded devices and in the browser and needs to store results on blockchain.


Client needs is an energy tokenization platform for prosumers. Prosume is in a joint-venture with multiple european technology partners, aimed at integrating the different functionalities and technologies offered by their respective platforms.

A key feature for Prosume is the computing of rewards for users who use (or not use) power when requested by the grid operator: the computation requires reading data from different sources (databases, APIs and MQTT brokers), has to run on low-specs embedded devices and needs to store results on blockchain.

Forkbomb process

Requirements analysis  

  • analyse the use case with the client
  • compiling a list of requirements
  • analyze the 3rd party technologies involved in the joint-venture
  • plan the execution

Implementation and solution development

  • assistance during the integration of Zenroom’s ecosystem components
  • implementation of features in the Zenroom’s ecosystem based on previous analysis
  • developed complex smart contracts based data and cryptographic flows

Quality assurance and project management

  • called weekly to determine the level of readiness for launching a project
  • implemented own tests for data integrity and cryptography
  • stress (load) testing and benchmarking

Ongoing support and continuous improvement

  • implemented improvements in Zenroom based on requests and feedback
  • continuous follow up for support, improvements and bug fixing

Forkbomb solution

The Prosume platform can now compute rewards for an arbitrary amount of households, reading data stored in multiple sources and organized in an ontology. The reward is calculated by calling an API, that takes the timeframe of the rewards as a parameter.

The API runs on servers as well as on embedded devices, the computation can also be executed on mobile devices or in the browser, using minimal resources.