## 2 Background  
Many smart home automation papers propose APIs or practical implementations of smart device use cases, employing protocols ranging from HTTP to MQTT to CoAP, which has also shown potential for home automation applications [21]. [PERSON] et al. [22] proposed and developed an API for smart home automation called qtoggle to control any IoT device in the smart home environment with a TCP/IP stack via HTTP requests, regardless of the type of smart object or device. [PERSON] et al. [23] proposed a framework to manage IoT devices in smart buildings using the serverless paradigm. Their proposed system consists of gas and humidity sensors and smart bulbs, and the serverless platform of choice was the OpenFaas platform. [PERSON] et al. [24] proposed a framework for fog computing in smart homes called Ziwi, which enables the coexistence of Zigbee and Wifi devices on the same smart home framework. MQTT is used for its small code footprint and for addressing compatibility between smart devices. The increasing usage of MQTT in machine-to-machine applications has been stressed by [PERSON] et al. [25], stemming from its lightweight design and its publish/subscribe architecture. Most frameworks employing this protocol require the implementation of security mechanisms (such as TLS) that add some extra overhead to the communication. As research on the topic of security in MQTT is increasing [26; 27], various recent papers have also focused on the implementation of new security mechanisms designed specifically for MQTT-based smart home environments [28; 29].  
Different recent works explored the potentiality of integrating Amazon Alexa or, more generally, voice services into the smart environment to enable interactive and accessible interfaces. [PERSON] et al. [11] proposes a distributed framework for smart homes that uses natural language processing (NLP) to develop a human/smart environment interface. Their solution introduces a fog node for the deployment of intelligent user interface (IUI) software to reduce the voice interface response delay and to decrease bandwidth load. [PERSON] et al. [30] analyzed different data fusion and techniques for work offloading in IoT applications, such as fog and edge computing, which can find use in different IoT fields, including smart homes. The interface is designed to understand domain-specific natural language to support under-resourced languages that lack available ASR software, such as Amazon Alexa. [PERSON] et al. [31] explored the possibility of using Amazon Alexa to build smart home services for the elderly or to enhance the effectiveness of existing services such as \"carebots\". [PERSON] et al. [32] proposed a framework that integrates voice assistants into smart offices for various tasks such as ambient control and interaction with various services.  
This paper proposes a very flexible framework for smart home automation that embeds a voice interface, while in addition evaluating the use of cellular technologies for the dispatching of MQTT messages for commands and status updates. The introduction of cellular communication in these frameworks, if carefully evaluated, can aid in the implementation of different services in home and kitchen appliances, enabling, for example, predictive maintenance and remote monitoring services to be built on top of said frameworks. The flexibility of the serverless model and the use of MQTT, which is the main middleware in the cloud technologies described above, allowed for the integration of the different services provided by AWS, including voice interaction services. Furthermore, NB-IoT has been evaluated to test its efficiency in serving a framework based on MQTT. The remaining part of this section describes the technologies used for the design, testing, and evaluation of the proposed framework, embedding a smart extractor fan prototype. The details of the implementation and fusion of the aforementioned technologies are detailed in Section 3.