### IoT Needs and Impact of the Deterministic K-Identification  
The evolving growth and development of technologies for IoT use cases have given rise to several applications where a reliable symbol transmission (the technical problem of Shannon) is less relevant. In particular, the 5G and 6G wireless communications systems in the horizon of IoT are expected to create new applications where the semantic and goal performing aspects of the messages are the key concern. Furthermore, these applications suffer other challenges, such as having difficulty coping with generation of randomness and working with sophisticated random number generators. Also, in some case, a strict criterion on the performance speed for recognition/identification of an event is imposed, or it is needed to deal with an increasing size of the search space. In the following, we expand on such challenges in more detail and suggest the K-identification problem as a promising approach for them. **Semantic and goal-oriented communications:** Let us define the K-identification problem considered in this paper as follows: Assume that the message set is \(\mathcal{M}=\{1,2,\ldots,M\}\), and message \(i\) is sent by the transmitter. Furthermore, assume an arbitrary subset of the message set with size \(K\) by \(K\). In the technical problem setting (symbol transmission), the receiver is interested in determining exactly which message is sent by the transmitter, i.e., to reconstruct the sent message. However, in the K-identification setting, the receiver is only interested in determining whether or not the sent message belongs to the set \(K\). In other words, the receiver decided \(i\in K\) or \(i\
otin K\) without stating exactly which message is sent. Note that, in principle, identification should be guaranteed for any goal identification message set \(K\subseteq\mathcal{M}\) of size \(|K|=K\), regardless of whether these identification message sets are intended for one or different receivers. In the K-identification problem, receiver seeks to perform a specific goal/task if its desired message sent at the transmitter, belongs to a set of \(K\) messages. Therefore, this problem may help to deliver the semantic aspects associated with the messages and can be adapted to the goal/task-oriented communications settings. That is, the K-identification problem can be a compelling candidate/answer to the IoT needs for applications defined in the context of PSC. These applications often ignore a reliable transmission of bits/symbols, and instead are alarm-triggered and demand to convey the semantic aspects of the messages. Potential applications of the K-identification problem for IoT systems are considered in [25]. **Randomness generation/management:** The original problem of K-identification proposed by [PERSON] in [26] considers employing randomness in the encoding module of a communication setup. That is, for each message at the transmitter, a unique distribution is assigned, which associates/maps the message to a codeword. This randomized mechanism for the K-identification problem allows for a remarkable gain in terms of the number of different messages (or/and their semantics/effects) that can be conveyed to the receiver, namely a double exponential behavior for the size of the message set; cf. [26] for details. Although in majority of use cases for IoT applications, such a double exponential behavior demand might be already real and steadily increasing, it has not necessarily been a focus point when launching an IoT device on the market. This occurs mostly because of cost and integration barriers. Specifically, in order to ensure standard realization of distributions in the encoding procedure, a true random number generator (TRNG) [27] should be embedded in IoT devices and utilized. Hardware-based TRNGs are often difficult to launch, manage and maintain for specific use cases [28]. These difficulties can be mitigated by exploiting deterministic codes in the system design for some of the applications.