Due to the increasing relevance of spatial information in different aspects of location-based services, various methods are used to collect this information. The use of crowdsourcing due to plurality and distribution is a remarkable strategy for collecting information, especially spatial information. Crowdsourcing can have a substantial effect on increasing the accuracy of data. However, many centralized crowdsourcing systems lack security and transparency due to a trusted party’s existence. With the emergence of blockchain technology, there has been an increase in security, transparency, and traceability in spatial crowdsourcing systems. In this paper, we propose a blockchain-based spatial crowdsourcing system in which workers confirm or reject the accuracy of tasks. Tasks are reports submitted by requesters to the system; a report comprises type and location. To our best knowledge, the proposed system is the first system that all participants receive rewards. This system considers spatial and non-spatial reward factors to encourage users’ participation in collecting accurate spatial information. Privacy preservation and security of spatial information are considered in the system. We also evaluated the system efficiency. According to the experiment results, using the proposed system, information accuracy increased by 40%, and the minimum time for reviewing reports by facilities reduced by 30%. Moreover, we compared the proposed system with the current centralized and distributed crowdsourcing systems. This comparison shows that, although our proposed system omits the user’s history to preserve privacy, it considers a consensus-based approach to guarantee submitted reports’ accuracy. The proposed system also has a reward mechanism to encourage more participation.

This paper presents the recent developments in the newly proposed KNTU robotic hand for improving its grasp capabilities as a dexterous robotic hand. This hand has three fingers (two 2-link fingers and a continuous one) that has the ability to grasp objects with different shapes. Each rigid finger is made up of two rigid links which are driven by cablesconnected to the motor. Also,both rigid fingers are installed on a rotary base which can configure them with respect to the continuous one thathas a fixed base. The continuous finger is controlled by three cables, each of them is connected to a separate motor. So the robotic hand has eight motors. This paper will describe the grasp planning for various objects by this robotic hand. First, an initial grasp configuration is planned according to the robotic hand structure with a good assortment of geometric shapes of objects. Four potentiometers on the links of rigid fingers are used for position control, also three encoders for continuous finger.Next,seven FSRs are used to measure the interactive force at the contact point in order to recognize the contact between the object and fingers. The microcontroller receives all the data to make a position control for all fingers. Finally, theproposed feedback control system isimplemented and obtained resultsare discussed.