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While the smart city gains global attention as a popular umbrella term for digitally enabled sustainable city development, city ad- ministrations are faced with the managerial challenge that comes with a strategic digital transformation. Smart city projects form the frontline of smart city strategies. In these smart projects, cities find a way to implement the principles of the smart city. Many of these are high-visibility projects with substantial budget implications, and therefore require scrutiny by means of a formal selection and evaluation process. In this research-in-progress paper we propose the outline for a project-level smart value assessment instrument. The instrument should serve at the same time as a tool for smart city managers to assess and plan upfront how a project will con- tribute to reach the city’s smart city ambition, as well as a post factum evaluation. The conceptual instrument has been developed in action-design research mode in collaboration with practitioners in the city of Brisbane, Australia and is demonstrated by mapping four smart city initiatives in different international contexts.

Aiming at rapid ship target detection and movement parameter estimation in high- resolution satellite image, this paper firstly analyzes marine and continental background image features. Furthermore, based on pixel gradient extraction and edge detection techniques, this paper extracts the ship target with the gradient map-based double threshold segmentation detection method. On the basis of utilizing three linear CCD shooting function of ALOS satellite, it finally proposes the method to rapidly estimate the movement parameter of the target ship by taking advantages of the long shooting interval.

A detailed spatially explicit evapotranspiration (ET) mapping at daily basis is of substantial benefit for agricultural water management. An integrated multi-sensor approach that combines the benefits of the high spatial resolution of Landsat and the high temporal resolution of MODIS and geostationary satellites to provide daily field-scale ET estimates is evaluated over two different agricultural landscapes. The ET data fusion methodology described here can provide detailed information about daily and seasonal water use patterns. This information can be of utility for irrigation managers at the scale of individual fields as well as for regional monitoring of water use toward allocation and conservation efforts.

Smart home barrier system is proposed and designed to keep people safe at home, especially for kids and pets. In this paper, working prototype of Internet of Things (IoT) enabled smart automatic door or barrier system is presented, where two models namely (i) monitoring model and (ii) actuated model can be switched to control access to the kitchen remotely by an online platform Ubidots. In experimental scenario, weight detection for monitoring model can measure from 0kg to 200kg with high precision. IoT environment enables door to be controlled remotely in real-time.

An important problem in robotics is to determine and maintain the position of a robot that moves through a previously known environment with reference points that are indistinguishable, which is made difficult due to the inherent noise in robot movement and identification of reference pints. Monte Carlo Localization (MCL) is a frequently used technique to solve this problem and its performance intuitively depends on reference points. In this paper we evaluate the performance of MCL as a function of the number of reference points and their positioning in the environment. In particular, we show that performance is not monotonic in the number of reference points and that a random positioning of the reference points is close to optimal.

The dangers of forest fires in Indonesia are now seen as a regional and even global disaster. This may result in smokes haze which can destabilize security in all sectors of the economy, including aviation. This research aims to detect haze using the brightness temperature of MODIS’ infrared channel. As known that the MODIS Aqua and Terra satellites are equipped by especially the infrared channel of wavelengths of 10.780 – 11.280 µ m (channel 31) and 11.770 – 12.270 µ m (channel 32) as well as of wavelength of 3.929 – 3.989 µ m (channel 22) and 4.020 – 4.080 µ m (channel 23) which could be utilized to estimate the brightness temperature and to understand how the surface temperature was occurred and distributed. In this case, the brightness temperature was measured using the multi-channel method. However, the radiance value of the NASA’s website data that is different from the brightness temperature of the LAPAN’s website data was converted by applying the Planck formula. The conclusions of the research show that there was a similarity spatial performance (digital imagery) of haze detection between both data sources, especially the data of 15 – 16 July 2018 and 6 – 7 August 2019. The spatial results of channels 22 – 23 described a lot of contact between the values of basic surface, fog, sandstorm, and smoke values. Meanwhile, the spatial result of channels 31 and 32 identified the majority contact of fog and cloud.

Due to their deployment flexibility, Unmanned Aerial Vehicles have been found suitable for many application areas, one of them being air pollution monitoring. In fact, deploying a fleet of Unmanned Aerial Vehicles (UAVs) and using them to take environmental samples is an approach that has the potential to become one of the key enabling technologies to enforce pollution control in industrial or rural areas. In this paper, we propose to use an algorithm called Pollution-driven UAV Control (PdUC) that is based on a chemotaxis metaheuristic and a Particle Swarm Optimization (PSO) scheme that only uses local information. Our approach will be used by a monitoring Unmanned Aerial Vehicle to swiftly cover an area and map the distribution of its aerial pollution. We show that, when using PdUC, an implicit priority is applied in the construction of pollution maps, by focusing on areas where the pollutants' concentration is higher. In this way, accurate maps can be constructed in a faster manner when compared to other strategies. We compare PdUC against various standard mobility models through simulation, showing that our protocol achieves better performances, by finding the most polluted areas with more accuracy, within the time bounds defined by the UAV flight time.

Bluetooth and WIFI channels are open to public users and have few security procedures. One security aspect is for a receiver to be able to verify the identity of the transmitter. This paper describes methods of identifying transmitters by the properties of their antennas.