Great Uuse-Cases for the DAO marketplace

In this blogpost we want to highlight a few examples of where the availability of a marketplace for IoT data can bring great value.

First question we need to ask, who will sell data?

There are a number of data sellers identified and the overview of the sectors already investing in sensors from Gartner highlights the key potential sellers of data for the years to come. The diagram below identifies the 2 groups (business, consumer) and the sub- groups that constitute each. It is clear that the business group is the main driving force in sensor deployment globally.

The business group is led by the following sectors:

Manufacturing and Natural Resources: the so-called industrial IoT consists of companies that are deploying sensors in order to improve operations. Their primary purpose for deploying sensors is to improve the efficiency of operations to reduce their cost base. DataBroker DAO presents the opportunity to sell selected data that will not reveal to competitors specifics of their manufacturing process.

Transportation: the data for transportation consists of both traffic and vehicle specific data. Traffic data includes for instance congestion and for instance data for shipping of goods like temperature sensors in food shipping containers. This also includes sensors for managing public transportation such as trains and busses. Vehicle specific data includes a wide array of sensors in cars and trucks both personally owned vehicles and fleets measuring everything from CO2 emissions to speed to preventive maintenance.

Utilities and Government: Utility providers deploy sensors for “smart” utilities en-masse to deliver more efficient utility services to their clients including smart grids and smart meters primarily for electricity and water. Government sensors are also wide ranging including everything from water level sensors to detect flooding, air quality monitoring to smart street lights.

In addition to these sellers which represent the bulk of currently deployed sensors, we identify at least 2 additional growth areas in the coming years:

Smart City Initiatives: a roadblock for getting smart city initiatives off the ground is the upfront cost of populating the town with sufficient sensors to be meaningful. The DataBroker DAO platform provides a means to turn what is today a sunk cost and a perpetual maintenance expense into an investment with a 2–3 year payback period and a continuous income stream after that.

Agricultural sector: in Belgium today, 10% of farmers are “techie”. They have a drone flying around and 5–20 sensors deployed and some other automation in place. The sensors include for instance wind, temperature, barometric pressure, humidity, PH level in the soil. They use these to manage their farm and spend between 10–50k euro per year, and DataBroker DAO will provide the possibility to recoup some of this cost.

Second question, who will buy this data?

Aside from the data processors in the ecosystem, any company looking to commercialise a product that is data driven is provided with the opportunity to develop the product without having to invest in the hardware. The potential buyers are extremely broad.

  • From the agricultural example above, two potential buyers jump out with > 1000 temperature sensors from nearly all regions of the country, the data is more accurate and granular than the national weather service. They are a potential buyer as are tv and radio stations who, by buying data directly on the marketplace, cut out the national weather service in their purchase from the farmers.
  • With >1000 PH level sensors covering most parts of the country, fertiliser companies would view this as a “honeypot” for their sales people.
  • Smart City Initiatives can limit the upfront cost of populating the town with sufficient sensors and turn the expense into an investment with a 2–3 year payback period and a continuous income stream after that.
  • Academics get access to the data from thousands of sensors and can buy data directly on the marketplace. This will result in a boost in the number of potential spin outs from academia as projects no longer have as high startup costs associated with buying and deploying a network of sensors.
  • Public Transport data can be sold to entrepreneurs who can help to create applications such as mobile apps to help the general public find the perfect routes to their desired destination, this introduces an extra revenue source for local governments while improving the infrastructure around the public transportation systems.
  • Self-driving technology companies could buy car sensor data to create the perfect self-driving AI and license this back to various car manufacturers.
  • Environmental agencies can gather data from millions of sensors around the world, such as PH water sensors, to get insights into environmental change, impact of their programs and understand where to act.
  • Energy corporations can purchase wind, weather & consumption data to plan new green energy initiatives and understand where to best place new wind or solar farms.

In short

The stakeholders in the IoT space have a lot to gain:

  • Sensor owners can monetize their data and turn a sunk cost into a potential money maker and at least the opportunity to recoup some of their investments in IoT sensors.
  • Network operators gain scale and speed in the adoption of their network as connected telcos can present a win-back to their enterprise accounts, a clear USP.
  • Sensor manufacturers can stop the “race to the bottom” for production and pull resources and capital out of manufacturing and allocate these to more successful SaaS offerings.
  • New types of buyers have unprecedented access to data and options to monetize their own data, in this category we see the entire booming and vibrant startup scene.
  • Data processors have an eco-system to sell their services to the right people.

Want to know more, talk to our Subject Mater Experts….

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