# Publish/Subscribe-Middleware-Based Intelligent Transportation Systems: Applications and Challenges
## 6 Challenges
### Privacy Challenges  
According to the UN [101], privacy is a fundamental human right recognized in numerous international treaties, including the right to avoid observation and to be left alone and the ability to keep one's thoughts, beliefs, identity, and actions confidential. Privacy also entails the right to decide and manage why, how, where, what, to whom, and when to disclose personal information. This perspective on privacy closely connects it to information (or data) protection. Privacy is also one of the potential challenges of publish/subscribe middleware in ITS. [PERSON] et al. [92] illustrated an example of this, where presence-based services (PSs) are services that act as \"watchers\" of a resource list. These services monitor the status of entities, known as Presentities, which are vehicle terminals that send status information. Vehicle terminals connect to only one PS, receiving all status information in the same notification. This situation may lead to watchers receiving unnecessary data about other services. The deployment and maintenance of sensors for ITS is expensive. Thus, researchers proposed using crowdsensing to collect data, actual vehicle positions, deviation from the static timetable, crowdedness information, vehicle condition, and road conditions [72; 73; 102]. Crowdsensing helps provide real-time data and connectivity in locations without network or ITS infrastructures. Commuters either input data manually \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Refs.** & **Middleware** & **Use Case** & **Real-Time** & **Scalability** & **Limitation** \\ \hline
[48; 49] & Apache Kafka & IoT traffic surveillance & Yes & High & High processing demands; \\  & & & & & dependent on continuous camera \\
[56; 57] & COPSS * & VANET black ice warnings & Yes & High & High RSU infrastructure cost \\
[59; 60] & CaaS * & V2V cooperation & Yes & Moderate & High complexity; requires dense \\  & & & & & vehicular presence \\
[58] & ITL System * & VANET traffic light alerts & Yes & High & Limited to infrastructure-based \\  & & & & intersections & \\
[65] & Spatio-Textual Pub/Sub * & RSN geo-textual filtering & Partial & Moderate & High computational cost for filtering \\  & & & & & at scale \\
[68] & LCM Pub/Sub * & Marine robotics & Yes & Moderate & Complex implementation; limited \\
[71] & MQTT & Land vehicles event monitoring & No & Low–Moderate & Requires reliable connectivity; single \\  & & & & & point of failure \\
[90] & MQTT & UAV swarm coordination & Partial & Moderate & MQTT unsuitable for mission-critical \\
[72; 73] & XMPP-based Pub/Sub * & Public transit crowdsensing & Yes & Moderate & Dependent on user input; potential \\  & & & & data inaccuracy & Complex integration; QoS tuning is \\
[74] & OPC UA + DDS + TSN & AVs in-vehicle communication & Yes & High & Complex integration; QoS tuning is \\
[81] & ROS + microRTPS Bridge & Drone–rover coordination & Yes & Moderate & Added latency and fragility under congestion \\
[12; 87] & OperSplice DDS & Train–station communication & Yes & High & Non-trivial QoS configuration \\
[15] & IIP Platform * & Road ITS client-cloud-P2P & Yes & Moderate & Mobile P2P matching is best-effort \\  & & & & only & \\
[92] & IMS Presence Service * & Road ITS fleet/status monitoring & Yes & Moderate & Server bottlenecks under heavy \\  & & & & subscriptions & \\
[98] & BONVOYAGE System * & Multimodal ITS using ICN & Yes & High & Complex architecture; QoS and \\  & & & & security need refinement \\ \hline \hline \end{tabular}
* Indicates custom-developed middleware tailored to a specific ITS use case.  
\end{table} 
Table 5: Comparative analysis of middleware solutions in ITS. or their smartphone sends its sensors' data to the ITS, where the service provider collects, aggregates, cleans, and analyzes the data to infer the public vehicles' status [73; 102]. However, participants send sensitive data like their location and preferred route, which poses a significant privacy challenge.