Search

There are situations when you need to accelerate the software development lifecycle. When the state of Kerala in India was devastated by severe flooding in 2018, we faced such a situation while we were building applications for managing rescue and relief operations during floods. We present a variant of DevOps called Rapid-DevOps to meet the need for accelerated release cycles while maintaining the required quality and stability. We describe the cost-benefit analysis to justify its use and the factors in our development process that enabled its successful adoption.

In this paper we present our experiences in designing, developing and deploying the essential components of effective disaster relief technology using the crowdsourced approach, based on our disaster relief platform named Amrita Kripa. We present both the technical and humanitarian aspects of Amrita Kripa. Amrita Kripa has been used in providing disaster relief during both 2018 and 2019 Kerala floods. We also share some of the feedback from various users during the disaster and how the feedback helped Amrita Kripa to evolve into a flexible, user-friendly and effective disaster relief platform. We also present a comprehensive comparison with other relief applications based on the crowdsourced approach.

Crowdsourced technology has been proven as effective communication mechanism in various disaster relief efforts worldwide. It often results in generating actionable and timely information regarding disaster situation, shelters, requirement for and availability of essential supplies such as food, clothing etc. But crowdsourcing has its downsides such as providing potentially inaccurate, incomplete and unverifiable information. We have developed and deployed a crowdsourced disaster relief mobile and web platform during 2018 and 2019 Kerala floods and provided relief to victims in the areas of rescue, medical help, supplies and services. During the deployment we experienced firsthand, both the positive and the negative aspects of crowdsourced approach. In this paper we detail our experiences and analysis and highlight some potential measures to mitigate the challenges in deploying crowdsourced technology.

Pervasive new advancements and internet connectivity have brought modern visions for medical diagnosis. Sensors on the patients' body can track parameters such as body temperature, pulse rate, and other medical signals in real time. Any abnormal deviations in the parameters can alert doctors to provide immediate attention. Marine fisherman travel into deep sea for their livelihood. They may stay up to a week, 100km away from land. During these times they are cut off from the land and do not have any support in case of emergencies. They often face issues such as sea sickness, mild fever and diarrhoea. We propose to develop a primary diagnosis device for marine fisherman and help them connect with doctors on the shore. We propose to build this device for the OceanNet marine communication infrastructure. The device will help doctors to diagnose the fisherman remotely and provide first level medical aid. Parameters such as heart rate, body temperature and respiration rate are captured by the device and sent to doctors using OceanNet network. Doctors can analyse the data and prescribe medicines to the fisherman. We also developed a mobile application which can suggest medicines if the device is unable to connect to a doctor immediately. In this paper, we discuss the architecture of the proposed diagnostic device. We have built a prototype of the proposed device and we discuss the results in this paper.

The World Health Organization (WHO) describes COVID-19 as a pandemic that is causing a worldwide health disaster. Wearing a face mask in public places is the most effective method to curb the spread of the virus. The Internet of Things is emerging as one of the most significant innovations and playing a vital role during the pandemic. Affordable remote health monitoring devices help doctors to track quarantined patients. Our government is trying its best to control the spread of the virus. Citizens who do not follow the protocols serve as the reason for these widespread infections. Our work proposes a system to identify protocol violators in real-time. Our system consists of a face mask detection module, a social distance monitoring module, and a non-contact temperature monitoring module. We intend to deploy our proposed approach in public places such as airports, schools, and hospitals. These modules depend on video feeds from general security cameras and IoT sensor nodes deployed around public areas. Health care and security officials can subscribe to real-time data feeds to track public behaviour.

In this paper, we propose a cost-effective framework for developing and testing autonomous toy RC cars. In addition, we present our on-going work on developing an autonomous toy RC car that is being built using the proposed framework.

Fishermen travel far up to 50 nautical miles into the ocean for fishing. They are often stressed and worried about their families as they cannot contact them for many days. Also, it is very difficult to pass any information regarding cyclone or other natural calamities to the fishermen. As there is no scope for mobile communication offshore beyond 8–9 nautical miles due to high operational expenses(OPeX). Traditional communication systems like Marine VHF radios and satellite phones are costly and restricted to only the boats in the ocean. This paper proposes a cost-effective, full duplex communication system for the marine fishermen to communicate among the boats in the ocean as well as with their families on the shore. This paper also presents the performance evaluation results of the system setup in a lab environment. The results obtained from the tests are satisfactory and the system can be implemented on the boats.

Coping with natural disasters is one of the central challenges of this century. Many disasters are accompanied by the collapse of buildings and other structures. Since, most of the rescue operations are manually executed, this, in turn, endangers the lives of the responders who are unaware of the situation inside the building. Exact localization of the trapped victims under the debris of collapsed buildings will help streamline the rescue operations. Use of UAVs to set up an aerial IoT to help in this effort is an area of ongoing research. The objective of this paper is to evaluate the various communication technologies that are best suited for such an application of IoT. Experiments were designed and performed under various scenarios to study the propagation effects through the debris, furniture, glass panels, etc. The communication technology alternatives were evaluated based on their coverage range, and throughput through various mediums such as concrete, metal, wood, glass, and air. This paper presents the results obtained and the inferences drawn from them.

Fishermen travel beyond 100km in trawlers for fishing and sometimes the trips last for a month. The cellular network coverage is limited to 15km from the shore. Fishermen are isolated from the shore, beyond 15km. Several hundreds of fishermen lost their lives during the recent cyclones in 2017 to 2019. This demands an efficient cost-effective and affordable communication system for marine applications. OceanNet can provide Internet Services in the ocean up to 100km. There is a lack of low cost and compact Wi-Fi access points for the current OceanNet System. This work proposes the design and development of a low-cost Wi-Fi access point for the OceanNet System and benchmarks the performance in comparison with the standard off the shelf WiFi Access Point.

OceanNet is a project to provide affordable offshore Internet service for marine fishermen during their fishing activities. The communication system onboard the fishing vessel consists of long-range (LR) Wi-Fi based Adaptive Backhaul Equipment (ABE) on the mast and Wi-Fi access point inside the deck. ABE can adapt its role to either client station or mobile base station to provide backhaul and fronthaul connectivity respectively. The directional antenna of the ABE tracks the base station. Fishermen can connect their mobile phones to Internet via the Wi-Fi access point to use social media apps such as WhatsApp, Skype, etc., for offshore communication. The automatic antenna reorientation platform reorients the directional antenna of the ABE towards the base station. The current deployed system has a potential reliability issue due to the moving parts in the reorientation mechanism and the possibility of misalignment of the directional antenna. This paper proposes an alternative solution for the current antenna reorientation system by using six ABEs to provide 360 o coverage. The role of each ABE needs to be switched dynamically to either client or base station or idle. We implemented the automated wireless mode switching of one ABE through python program using a Raspberry Pi board. The detailed implementation process is discussed in the paper.

Internet of Things (IoT) is an integrated technology in which billions of devices are capacitated with digital intelligence to interconnect and communicate through the Internet, for the fulfillment of various needs obviating human intervention. Communication technologies play a vital role in the design of IoT networks, in both indoor and outdoor applications. This work presents an in-depth study on the application of the sub-GHz frequencies (915 MHz and 868 MHz) over the widely used 2.4 GHz channel, for the design of low-cost IoT networks for indoor mission-critical applications. These frequency bands were experimentally evaluated, under varying indoor environments. In addition, a mathematical model for the computation of path loss exponent, in an indoor scenario affected by random interference by movements of humans as the environmental condition, is also proposed in this paper.

Marine environment can be very extreme and unpredictable. fishing vessels need a robust communication infrastructure to connect to the shore based services during scenarios such as impending cyclones and other emergencies (such as accidents with ships) to expedite rescue operations. Even operation-wise, Internet at sea would enable the availability of several applications and services (E-commerce, Live data of Potential Fishing Zones advisory, etc.) which would lead to a more improved and efficient fishing business for fishermen. The potential of the proposed OceanNet architecture for marine Internet connectivity is demonstrated through this V2I communication infrastructure that ensures connectivity and coverage to satisfy the vehicular application requirements. This work is a study of link quality parameters based on real data collected from the installed OceanNet devices on eight fishing nodes. The ultimate aim of such a study is to be able to provide information for fishermen as to the locations where they would get reliable Internet connectivity for emergency communication using VoIP services.

Social media has been a critical factor in providing improved disaster relief across the world in the past 15 years. However, our analysis of Chennai flood relief efforts revealed many downsides to the relief efforts based on social media such as inaccurate, inconsistent, incomplete, and stale information, user anonymity, information misuse, lack of geographical information etc. To address these issues, we propose the following technical, security, and operational considerations for building a robust disaster relief application. We classify the technical considerations into performance and resilience. Security considerations cover data integrity, trust, and privacy. Operational considerations include multilingual support, GIS support, data organization, live status updates, and disaster boundary demarcation. We illustrate these considerations in the context of Amrita-Kripa, a disaster relief application based on crowdsourcing. Amrita-Kripa was deployed during 2018 and 2019 Kerala floods and provided relief to thousands of victims.

Crowdsourced approach using mobile phones towards rescue and relief operations in post-disaster situations is becoming popular. The mobile phones play a critical role in estimation, evacuation and relief operations as they can be used for sensing and transmitting information such as location, elevation, acceleration, images and other user generated messages, but the mobile IoT edge devices are often resource constrained by battery and network. In this paper we present AROM, an Adaptive Resource Optimization Model for optimizing mobile sensing and communication systems, by considering network and battery constraints. AROM works by adaptively computing a resource criticality score and controlling sensing mechanisms and throttling and prioritizing network communications based on the score. We also present the details of performance tests done to validate our model and the analysis of results. We have implemented this architecture in our Amrita-Kripa disaster relief application which was deployed during 2018 and 2019 Kerala floods for rescues and relief activities.

Tracking the location of fishing boats in real-time had been a major concern to families and administrators. The solutions available in the market are either too costly or do not provide real-time tracking. The IoS and Android mobile phones put a lot of restrictions on background location tracking, which makes them unreliable for continuous real-time tracking. A low cost, embedded, real-time location tracking system, built using Raspberry Pi, and GPS sensor onboard, communicating with the server on the shore using long-range WiFi backhaul. This boat tracker system runs on Linux OS, embedded NodeJS server and OceanNet network. This was implemented in 10 boats and has been working for over a year successfully. In this paper, the hardware and software design aspects of the lightweight, network-fault-tolerant, real-time OceanNet boat tracking system along with an analysis of its performance are presented.