In the past few years, Internet of Things (IoT) has emerged as an outstanding technology and can be considered as the backbone of the smart world era as it connects physical devices with the internet. On the other hand there are these intelligent conversation interfaces that use a dialogue system to have a conversation with the users and are already used widely. In this paper, we focus on integration of chatbots and IoT to address a critical problem like air quality awareness. We present the architecture of the chatbot and its implementation on an instant messaging application. The chatbot not only provides air quality, temperature and humidity information to the users but also provides services like subscription to air quality monitoring nodes in a particular area or any part of the service region, alarm services, threshold settings, geoquery and recommendation based on the pollutant levels. A detailed explanation of the scenario of use, challenges identified during development process and possible future directions of this integration have also been addressed.

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Mobile social networks (MSNs) enable users to discover and share contents with each other, especially at ephemeral events such as exhibitions and conferences. Nevertheless, the incentive of users to actively share their contents in MSNs may be lacking if the corresponding cost is high. In this paper, we propose a content pricing and sharing framework in MSN that is built on users' collective bidding and content cost sharing. The content sharing problem is formulated as a distributed system that achieves cooperative outcome while preserving non-cooperative decision making among the users through the proposed collective bidding and broadcast nature of wireless communication. That is, co-located peers individually propose payments to their encounters whose contents they are interested in based on their perceived values of the contents. The respective content owners share their contents if the proposed payments can collectively compensate the cost of sharing their contents with these peers. We show that this guarantees individual rationality and promotes content sharing among the opportunistic encounters in the network. Performance evaluation shows that the proposed mechanism reduces the time and cost to collect contents of interest in the network and significantly improves network utilization.

There is a growing concern over the issues related to online privacy due to large availability of high quality images. To tackle the privacy concerns a face swapping application is proposed. There is a library of face images, which is created by downloading images from different sources on Internet. For any given image, first of all facial landmarks are detected. The second image is rotated and scaled so that it can properly fit over the input image. To make sure that the new image looks natural, color balance adjustment is done. After that blending of features from the second image onto the input image is done. It is also shown how this system can be used to creating appealing and funny photographs for entertainment purposes. We conclude with a study that shows the high quality of images produced by this system as compared to existing face swap applications and also limitations of this system.

In this paper, we present an energy, data and cost efficient model for mobile opportunistic PM2.5 sensing via bicycles. To facilitate the implementation of such systems, we first investigate the accuracy issue of different Inertial Monitoring Unit (IMU) built into the Arduino 101 for stop detection. Then, by curve fitting and optimization calculation on system parameter tuning and modeling, each sensor could start up at the optimum time in order to achieve minimum energy consumption and maximum data usability. Also we propose a formula that can count the minimum number of required PM2.5 sensors under the condition of total experiment time spent and total expected number of sampling point. Finally, we conduct a field experiment to evaluate the proposed model in a real world setting. The results show that total time spent of PM2.5 data collection is similar to the expected time derived from the system modeling.

When stricken by a catastrophic natural disaster, emergency rescue operation is very critical to many lives. Many people trapped in the disastrous areas under collapsed buildings or landslides may have a large chance to survive if they are rescued in "Golden 72 Hours". Victims rescued from the debris and evacuated from their home jammed in shelters need life support material to support their lives. They also need to communicate to each other for various reasons. However, communication systems were usually down due to various reasons. The loss of communication systems and information networks made the rescue and relief operation extremely difficult. Many people died before they got a chance to be rescued. This paper analyzes the causes that paralyzed the entire communication systems in Jiji/Taiwan Earthquake and proposes a MANET based communication platform as well as a Rescue Information System for Earthquake Disasters that can support a large number of rescue volunteers under catastrophic natural disasters.

In Wireless Mesh Networks(WMNs), users can enjoy the real-time video streaming service anytime and anywhere through the service. Compared to the client/server model, the P2P(Peer-to-peer) approach is more suitable for video streaming applications because of its efficient usage of network resources. However, the multimedia applications are very sensitive to delay time and the performance of packets transmission which is significantly influenced by the co-channel interference. In our approach, we choose the better quality links for routing instead of the minimum hop-count path in MAODV(Multicast Ad hoc On-demand Distance Vector). Then we distribute the video streaming to receivers by using multicasting in multi-channel WMNs, and modify the MAODV routing protocol to construct two disjoint multicast trees as the backbone for the P2P structure. Therefore, we can adopt the MDC(Multiple Description Coding) scheme to encode the video into two independent sub-streams and transmit separately along these trees. Experiment results show that in higher traffic load environment, our scheme is more effective to reduce the latency and improve overall system performance.

This paper proposes a MANET/VANET based group communication system, P2Pnet, to support the communication and information demand for mobile group users such as rescue teams in catastrophic disasters, army in battle fields, and mobile learning groups. We use the Jiji Earthquake as an example to illustrate the physical environment and to establish system requirements for a mobile group communication system that are suitable for the environments mentioned above. We have implemented the first phase prototype as well as two application experiments on top of P2Pnet: Rescue Information System for Earthquake Disasters (RISED) and a mobile English learning experiment conducted in the Nation Chengchi University.

It is suggested that emotion plays a significant role in rational and intelligent behaviors. People behave emotions in different ways, and may not be noticeable through outside appearances. However, physiological information may reveal the clue for emotions. We proposed a mobile personal emotion monitoring system design, and proposed an adaptive algorithm that can help recognize user's emotion stateby using physiological sensors. We applied the dimensional analysis approach and adopted IAPS (International Affective Picture System) to manipulate psychological experiments. We also proposed an emotion recognition learning algorithm. It would extract each pattern of emotions from cross validation training and can further learn adaptively by feeding personalized testing data. We measured the learning rate of each subject which reveals incremental enhancement. Furthermore, we adopted a dimensional to discrete emotion transforming concept for validating the subjective rating. Compared to the experiment results of related works, our system outperforms both in dimensional and discrete analyses. Most importantly, the system is implemented based on wireless physiological sensors for mobile usage. This system can reflect the image of emotion states in order to provide on-line smart services.

The IEEE 802.16 standard was designed for Wireless Metropolitan Area Network (WMAN). It supports QoS and has very high transmission rate. The key part of 802.16 – packet scheduling, was undefined and is an open issue. We first proposed a token-bucket based uplink packet scheduling combined with call admission control (CAC) of 802.16. Then a model of characterizing traffic flows by token bucket is presented. The simulation results show that our CAC and uplink packet scheduling can promise the delay requirement of rtPS flows and our model can predict the delay and loss of a traffic flow precisely.

Quality of service (QoS) support in wireless LAN (WLAN) is the main mission of the IEEE 802.11 group e. It uses enhanced distributed channel access (EDCA) to differentiate service of priorities by means of various inter-frame spaces (IFS) and contention windows (CW). In order to efficiently manage QoS for the IEEE 802.11e networks, throughput and MAC delay for several traffic flows from 4 different access categories (AC) should be more accurately estimated. A four-dimensional Markov model is proposed to evaluate these. The correctness of our analysis has been validated via simulation results. Throughout our model, call admission control (CAC) can be easily applied, and thus resource management for QoS support for multimedia applications is well achieved.

We present a prototype for a new architecture, MCN (multihop cellular network), implemented over a wireless LAN platform. MCN preserves the virtue of traditional single-hop cellular networks where the service infrastructure is constructed by many bases, but it also adds the flexibility of ad-hoc networks where wireless transfer through mobile stations in multiple hops is allowed. The MCN can reduce the number of required bases or improve the throughput performance. On IEEE 802.11 compliant wireless LAN products, a bridging protocol, our BMBP (base-driven multihop bridging protocol), runs between mobile stations and access points to build bridging tables. The demonstration shows that MCN is a feasible architecture for wireless LANs.

We present a method to compute the path bandwidth for the DSDV (destination-sequenced distance-vector) based routing algorithm. The addressed network does not necessarily have a cellular structure and could have no fixed infrastructure. This network can be either stand-alone, or connected to the wired network. Each mobile station has to relay packets for others, thus achieving multihop routing. To calculate the available bandwidth of a path in this environment, it is incorrect to simply compute the minimum bandwidth of the links along the path. There are two crucial steps in the path bandwidth computation process of this multihop environment: (1) intersecting the sets of common free slots of two adjacent links, and (2) dividing the intersection for the adjacent links to share. We present two bandwidth computation rules including the half rule and the floating rule. Numerical results are given to evaluate the performance of applying these rules to the DSDV-based QoS routing algorithm.

Applications to be supported on broadband networks exhibit a wide range of traffic statistics and many of them are sensitive to delay and loss violations. To accurately estimate admissible workload and bandwidth requirement, a detailed traffic model, HAP (Hierarchical Arrival Process) is proposed in this paper. Packets generated from HAP are modulated by processes at user, application, and message levels. This model is a generalization of on-off traffic models and is shown to be equivalent to a special class of MMPP (Markov Modulated Poisson Process). Three algorithmic methods along with simulations are applied to evaluate the queueing performance under HAP traffic. Delay under HAP traffic can be well over tens of times higher than Poisson traffic, depending on parameters and load. Congestion may persist for minutes. HAP's dramatic short-term behavior explains the occasional congestion in the real networks. Conventional traffic models, however, do not exhibit this behavior. With these results, we give implications for broadband network control.