LoRa-based Alert System for Public-safety

This paper presents a novel closed loop architecture for citizen security using LoRa based devices. The proposed system comprises of a custom made end-device which can be connected to street light poles in an area and a gateway device which can be connected at a large distance from the end-devices. LoRa physical layer is used as the main communication interface which enables large distance transmission. A data logging server is used for logging the node-id everytime it is pressed. Data is uploaded to the server using a 4G-LTE dongle. An android app is also developed which shows the location of the pressed node and provides navigation routes to the concerned security person to reach that node. We have compared our network operation with commercially avilable security devices. Power consumption and cost are the two metrics chosen for evaluation. Results show that our network is extremely low-cost and low-powered than existing solutions

Mobile Robot Terrain Mapping for Path Planning using Karto Slam and Gmapping Technique

Mapping is one of the mobile robot's most basic applications. A mobile robot's sensors, such as a laser sensor, sonar, and camera, are used to create the map. Most mapping techniques use simultaneous localization and Mapping (SLAM). SLAM allows for creating a map and the localization of the robot's position on it. This research compares the trajectories of a mobile robot created by several ROS-based SLAM systems. And also, GMapping and Karto SLAM are two well-known SLAM algorithms employed. The mobile robot is equipped with 2D lidar and monocular camera. The mapping is done at two distinct locations, in labs of varying sizes with varying numbers of static and dynamic objects. Three test runs are conducted for GMapping to examine the effects of various variables on mapping quality, including particle filter, mapping delay, and robot speed. The results show a significant difference in operation completion time and mapping accuracy as a result of the parameter changing over the three test runs. Due to the improved accuracy of the parameter used in the second test run of GMapping and Karto SLAM, the accuracy of the maps is the basis for this improvement. On the other hand, the second test run with robot particle filter 30, mapping delay 1, and speed 0.13m/s is thought to be the best3\2 13Q/0. © 2022 IEEE