## 4 Approach  
The methodology proposes the use of two decision-making tools in the selection of buyers (citizens) which evaluates the different alternatives and helps the decision-maker (smart governance) to select the citizen who will be awarded the smart home. For this methodology, the AHP tool is used to analyze the structure of the buyer selection problem and to determine the weights of the criteria or attributes, and the TOPSIS tool is used to select buyers (citizens) and obtain the final classification of buyers. The AHP determines the weighted weights of the decision criteria based on a set of already defined criteria and the preferences of the decision-maker (smart governance) on each of these, which helps to reduce the complexity of decisions. TOPSIS chooses the alternatives (buyers) that have the shortest distance from the ideal solution and the farthest distance from the negative-ideal solution. This tool takes as the input the values obtained from the evaluation process for each criterion together with its weight.  
AHP allows you to convert qualitative values into quantitative ones, compare preferences between criteria, and calculate criteria weights across preferences. While TOPSIS allows you to find the best alternative using a simple mathematical process, and also calculates the distances of a set of alternatives against an ideal and negative-ideal solution; in this way, the number of alternatives is not a problem.  
A smart city should try to be fair and equitable in dealing with citizens or, at least, give them the same opportunities. We must mention that, with this work, we do not intend to question the free supply and demand that governs the world economy. We propose a model for a smart city in which a group of potential buyers (citizen) enters a selection process, and the highest bidder acquires the desired property, as shown in Figure 5.  
Following the steps:  
* A buyer searches and finds the house. The buyer searches online or offline for the house he wants to buy. Here, the Smart city can intervene, offering its respective properties.  
Figure 5: General model proposed.  
Buyers (citizens) join in the group, every buyer has attributes; this is the most important part because here the proposed model is focused and it is assumed that there are \"n\" interested in acquiring a certain property. In the current model, shown above, (Figure 1) a merely economic negotiation is made. If both parties agree, the deal is closed and the regular procedure indicated by law is followed. However, in our work, this is a model where money, age, behavior, as well as the environment, etc. are factors that influence the acquisition of real estate. A smart home should be able to decide who will be its owner, avoiding or reducing bureaucracy, corruption, abuse of power, etc.
* The smart contract decides the winner. A smart contract will be generated without the intervention of third parties that may influence or modify the result (Figure 6). Upon fulfilling certain criteria, the ranking will determine the entry requirements for the next smart contract.
* The citizen winner transfers cryptocurrency and the smart contract records his/her name in the blockchain (change the owner). Another smart contract should read the name of the person authorized to make the payment; it should only accept payment from that individual and reject any other. Once the transaction is finished, the data of the new owner is written into the blockchain, complying with the laws in force in the country, giving full and unrestricted access to all services to the new owner.
* The new owner can access his/her home. The new owner requests access to the property, this home acts as an IoT, receives the request, reads the blockchain, and approves or denies access to the individual.