## 1 Introduction
### Distributed Ledger Technologies  
Distributed databases or distributed ledgers, such as blockchain [8], are managed via a consensus process by nodes in a peer-to-peer network. Despite the fact that all peers participate in maintaining database integrity, this consensus approach eliminates the necessity for a central administrator. Individuals may reclaim control over their data due to the lack of a central controller. Blockchain was introduced in 2008 [9] as a distributed ledger technology that is decentralized and immutable. These attributes ensure that the data stored on the blockchain is secure, authentic, and distributed among all the peers in the network. There is no third party involved while making transactions on this technology and no central authority that can control it. These features open the door to various application domains and research areas such as IoT, healthcare, environment monitoring, AI, deep learning, security, and IoT data integrity, wherein the data needs to be distributed and tamper-resistant [10] to avoid a single point of failure when stored on a centralized database. However, blockchain technology is facing several technical challenges despite having a great potential for the construction of future Internet systems [11]. The main challenge or concern is the scalability of blockchain. The time taken to mine a block is about 10 min and the block size is limited to 1 MB only. Moreover, the bitcoin blockchain is not able to deal with high-frequency trading since it is limited to 7 transactions per second. Additionally, the propagation of the blocks will be slow [12] if the block size is large, as it will require more storage space. Since few users would wish to maintain such a large blockchain, this will lead to centralization. Hence, it has been a tough challenge to address the tradeoff between block size and latency. Moreover, there is the possibility of selfish mining strategies, whereby miners can access greater rewards than they are entitled to. In this paper, we have leveraged environmental sensory telemetry data, which consists of various sensory data parameters such as temperature, humidity, CO, liquid petroleum (LPG), smoke, light, and motion. The data was generated by a series of three customized sensor arrays. Sensor arrays, consisting of an MQ135 hazardous gas detection sensor, DHT22 temperature and humidity sensor, Onyehn IR pyroelectric infrared PIR motion sensor detector, and Anombest light intensity detection photosensitive sensor were connected to Raspberry Pi sensory devices. Moreover, these devices were placed in distinct physical locations and variable environmental conditions, as shown in Table 1.  
Each of these IoT devices is continuously collecting the sensory values from four sensors at a standard interval of 5 s. The data was collected during the span of \"from 07/12/2020 00:00:00 UTC-07/19/2020 23:59:59 UTC\" with a total number of \"405,184 rows\". In this framework, the \"ISO standard Message Queuing Telemetry Transport (MQTT)\" protocol [13] is leveraged to bind the sensory readings, a unique ID, and a timestamp and broadcast in terms of a single message; a sample payload is shown in Figure 1.  
Different consensus protocols and network topologies have been investigated; these are distributed to ensure the integrity of a distributed ledger while providing high transactions per second and zero fees for transactions. Algorand [14], IOTA [15], Hashgraph [16], and Ouroboros [17] are a few prominent protocols that promise to accomplish the aforementioned characteristics. This technology is suitable not just for the future of electronic finance but also for every data-driven industry. In this paper, we propose an environmental monitoring [18] application of IOTA, which will allow environmental professionals, such as environmentalists and environmental officers, to share and store encrypted IoT sensor data in a secure way for monitoring purposes. IOTA is a permissionless distributed ledger protocol with no transaction fees.